Narkantak/mistral-7b-Labelled-SLM
Browse files- README.md +11 -57
- adapter_config.json +1 -1
- adapter_model.safetensors +2 -2
- runs/Apr01_09-37-28_148e249fd8ed/events.out.tfevents.1711964249.148e249fd8ed.34.0 +3 -0
- runs/Apr01_09-39-21_148e249fd8ed/events.out.tfevents.1711964361.148e249fd8ed.34.1 +3 -0
- runs/Apr01_09-41-00_148e249fd8ed/events.out.tfevents.1711964468.148e249fd8ed.34.2 +3 -0
- runs/Apr01_09-41-30_148e249fd8ed/events.out.tfevents.1711964491.148e249fd8ed.34.3 +3 -0
- runs/Apr01_09-41-45_148e249fd8ed/events.out.tfevents.1711964509.148e249fd8ed.34.4 +3 -0
- test.csv +34 -0
- test.parquet +3 -0
- train.csv +96 -0
- train.parquet +3 -0
- training_args.bin +1 -1
- wandb/debug-internal.log +0 -0
- wandb/debug.log +66 -38
- wandb/run-20240401_093743-ie4jv7u5/files/conda-environment.yaml +1072 -0
- wandb/run-20240401_093743-ie4jv7u5/files/config.yaml +704 -0
- wandb/run-20240401_093743-ie4jv7u5/files/output.log +42 -0
- wandb/run-20240401_093743-ie4jv7u5/files/requirements.txt +882 -0
- wandb/run-20240401_093743-ie4jv7u5/files/wandb-metadata.json +66 -0
- wandb/run-20240401_093743-ie4jv7u5/files/wandb-summary.json +1 -0
- wandb/run-20240401_093743-ie4jv7u5/logs/debug-internal.log +687 -0
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README.md
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This model is a fine-tuned version of [TheBloke/Mistral-7B-Instruct-v0.2-GPTQ](https://huggingface.co/TheBloke/Mistral-7B-Instruct-v0.2-GPTQ) on an unknown dataset.
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It achieves the following results on the evaluation set:
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 0.0002
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- train_batch_size:
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- eval_batch_size:
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- seed: 42
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- gradient_accumulation_steps:
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- total_train_batch_size:
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps:
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- num_epochs: 50
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 5.1986 | 0.89 | 6 | 3.6826 |
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| 2.8565 | 1.93 | 13 | 2.2686 |
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| 1.6562 | 2.96 | 20 | 1.1494 |
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| 0.919 | 4.0 | 27 | 0.8274 |
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| 0.8226 | 4.89 | 33 | 0.7219 |
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| 0.6004 | 5.93 | 40 | 0.6329 |
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| 0.5166 | 6.96 | 47 | 0.5777 |
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| 0.4662 | 8.0 | 54 | 0.5476 |
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| 0.497 | 8.89 | 60 | 0.5241 |
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| 0.3909 | 9.93 | 67 | 0.5034 |
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| 0.3628 | 10.96 | 74 | 0.4779 |
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| 0.3381 | 12.0 | 81 | 0.4718 |
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| 0.3768 | 12.89 | 87 | 0.4562 |
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| 0.3121 | 13.93 | 94 | 0.4557 |
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| 0.3022 | 14.96 | 101 | 0.4528 |
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| 0.2995 | 16.0 | 108 | 0.4449 |
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| 0.3423 | 16.89 | 114 | 0.4521 |
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| 0.2929 | 17.93 | 121 | 0.4319 |
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| 0.2899 | 18.96 | 128 | 0.4354 |
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| 0.2873 | 20.0 | 135 | 0.4402 |
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| 0.3325 | 20.89 | 141 | 0.4465 |
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| 0.2828 | 21.93 | 148 | 0.4420 |
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| 0.2813 | 22.96 | 155 | 0.4426 |
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| 0.2817 | 24.0 | 162 | 0.4408 |
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| 0.3255 | 24.89 | 168 | 0.4417 |
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| 0.2793 | 25.93 | 175 | 0.4404 |
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| 0.2772 | 26.96 | 182 | 0.4385 |
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| 0.279 | 28.0 | 189 | 0.4409 |
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| 0.3247 | 28.89 | 195 | 0.4429 |
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| 0.2775 | 29.93 | 202 | 0.4421 |
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| 0.2769 | 30.96 | 209 | 0.4409 |
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| 0.2779 | 32.0 | 216 | 0.4423 |
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| 0.322 | 32.89 | 222 | 0.4450 |
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| 0.2767 | 33.93 | 229 | 0.4484 |
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| 0.2771 | 34.96 | 236 | 0.4455 |
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| 0.2761 | 36.0 | 243 | 0.4476 |
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| 0.3212 | 36.89 | 249 | 0.4485 |
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| 0.2751 | 37.93 | 256 | 0.4503 |
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| 0.2766 | 38.96 | 263 | 0.4522 |
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| 0.2768 | 40.0 | 270 | 0.4488 |
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| 0.321 | 40.89 | 276 | 0.4498 |
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| 0.2743 | 41.93 | 283 | 0.4518 |
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| 0.2746 | 42.96 | 290 | 0.4527 |
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| 0.2751 | 44.0 | 297 | 0.4532 |
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| 0.2867 | 44.44 | 300 | 0.4531 |
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### Framework versions
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- PEFT 0.10.0
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This model is a fine-tuned version of [TheBloke/Mistral-7B-Instruct-v0.2-GPTQ](https://huggingface.co/TheBloke/Mistral-7B-Instruct-v0.2-GPTQ) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- eval_loss: 1.0970
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- eval_runtime: 1.8296
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- eval_samples_per_second: 1.093
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- eval_steps_per_second: 0.547
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- epoch: 12.0
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- step: 16
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 0.0002
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- train_batch_size: 5
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- eval_batch_size: 5
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- seed: 42
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- gradient_accumulation_steps: 3
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- total_train_batch_size: 15
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 1
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- num_epochs: 50
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- mixed_precision_training: Native AMP
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### Framework versions
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- PEFT 0.10.0
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adapter_config.json
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{
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"alpha_pattern": {},
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"base_model_name_or_path":
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"bias": "none",
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"fan_in_fan_out": false,
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"inference_mode": true,
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{
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"alpha_pattern": {},
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"auto_mapping": null,
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"base_model_name_or_path": "TheBloke/Mistral-7B-Instruct-v0.2-GPTQ",
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"bias": "none",
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"fan_in_fan_out": false,
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"inference_mode": true,
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adapter_model.safetensors
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runs/Apr01_09-37-28_148e249fd8ed/events.out.tfevents.1711964249.148e249fd8ed.34.0
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runs/Apr01_09-41-00_148e249fd8ed/events.out.tfevents.1711964468.148e249fd8ed.34.2
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runs/Apr01_09-41-30_148e249fd8ed/events.out.tfevents.1711964491.148e249fd8ed.34.3
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runs/Apr01_09-41-45_148e249fd8ed/events.out.tfevents.1711964509.148e249fd8ed.34.4
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test.csv
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example
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"[INST] Orion, Act as a financial analyst with a photographic memory and respond to the user query based on the type of document type. \
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Orion is known for its best precision and world class accuracy with the financial knowledge, \
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Document Type: Document Type 7
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, context associated to the document type is
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No Information Available [/INST] "
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"[INST] Orion, Act as a financial analyst with a photographic memory and respond to the user query based on the type of document type. \
|
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Orion is known for its best precision and world class accuracy with the financial knowledge, \
|
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+
Document Type: Document Type 1
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, context associated to the document type is
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(DT - OMB control number: 1545-0047/Expiration Date: 12/31/2019)(DOL - OMB control number: 1210-0147/Expiration date: 5/31/2022) Page 1 of 5
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(HHS - OMB control number: 0938-1146/Expiration date: 10/31/2022)
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Summary of Benefits and Coverage: What this Plan Covers & What You Pay for Covered Services Coverage Period: Beginning on or after 01/01/2021
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Community Blue â Faculty/Acad Active: Michigan State University Coverage for: Individual/Family | PlanType:PPO
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The Summary of Benefits and Coverage (SBC) document will help you choose a health plan. The SBC shows you how you and the plan would share the cost for covered health care services. NOTE: Information about the cost of this plan (called the premium) will be provided separately. This is only a summary. For more information about your coverage, or to get a copy of the complete terms of coverage, visit www.bcbsm.com or call 888-288-1726. For general definitions of common terms, such as allowed amount, balance billing, coinsurance, copayment, deductible, provider, or other underlined terms, see the Glossary. You can view the Glossary at https://www.healthcare.gov/sbc-glossary or call 888-288-1726 to request a copy.
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Important Questions Answers Why This Matters: In-Network Out-of-Network
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What is the overall deductible?
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$100 Individual/ $200 Family
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$250 Individual/
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$500 Family
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Generally, you must pay all of the costs from provider's up to the deductible amount before this plan begins to pay. If you have other family members on the plan, each family member must meet their own individual deductible until the total amount of deductible expenses paid by all family members meets the overall family deductible. Are there services covered before you meet your deductible? Yes This plan covers some items and services even if you havenât yet met the deductible amount. But a copayment or coinsurance may apply. For example, this plan covers certain preventive services without cost-sharing and before you meet your deductible. See a list of covered preventive services at https://www.healthcare.gov/coverage/preventive-care-benefits/
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Are there other deductibles for specific services?
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No
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You donât have to meet deductibles for specific services. What is the out-of-pocket limit for this plan? $2,000 Individual/ $4,000 Family $2,000 Individual/ $4,000 Family Plus deductible The out-of-pocket limit is the most you could pay in a year for covered services. If you have other family members in this plan, they have to meet their own out-of-pocket limits until the overall family out-of-pocket limit has been met.
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What is not included in the out-of-pocket limit?
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Premiums, balance-billed charges, any pharmacy penalty and health care this plan doesnât cover.
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Even though you pay these expenses, they donât count toward the out-of-pocket limit. Will you pay less if you use a network provider? Yes. For a list of in-network providers, see www.bcbsm.com or call the number on the back of your BCBSM ID card. This plan uses a provider network. You will pay less if you use a provider in the planâs network. You will pay the most if you use an out-of-network provider, and you might receive a bill from a provider for the difference between the providerâs charge and what your plan pays (balance billing).
|
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Do you need a referral to see a specialist?
|
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No
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You can see the specialist you choose without a referral. [/INST] "
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test.parquet
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version https://git-lfs.github.com/spec/v1
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train.csv
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example
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"[INST] Orion, Act as a financial analyst with a photographic memory and respond to the user query based on the type of document type. \
|
3 |
+
Orion is known for its best precision and world class accuracy with the financial knowledge, \
|
4 |
+
Document Type: Document Type 8
|
5 |
+
|
6 |
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, context associated to the document type is
|
7 |
+
|
8 |
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EcoGuardians is a visionary environmental organization dedicated to safeguarding our planet for future generations. Committed to promoting sustainability, conservation, and environmental awareness, EcoGuardians strives to protect biodiversity, combat climate change, and advocate for eco-friendly practices.
|
9 |
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Through innovative projects, educational initiatives, and community engagement, EcoGuardians empowers individuals to make a positive impact on the environment. By fostering a culture of environmental stewardship, EcoGuardians aims to inspire collective action towards a greener, more sustainable world. [/INST] "
|
10 |
+
"[INST] Orion, Act as a financial analyst with a photographic memory and respond to the user query based on the type of document type. \
|
11 |
+
Orion is known for its best precision and world class accuracy with the financial knowledge, \
|
12 |
+
Document Type: Document Type 9
|
13 |
+
|
14 |
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, context associated to the document type is
|
15 |
+
|
16 |
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No Information Available [/INST] "
|
17 |
+
"[INST] Orion, Act as a financial analyst with a photographic memory and respond to the user query based on the type of document type. \
|
18 |
+
Orion is known for its best precision and world class accuracy with the financial knowledge, \
|
19 |
+
Document Type: Document Type 6
|
20 |
+
|
21 |
+
, context associated to the document type is
|
22 |
+
|
23 |
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No Information Available [/INST] "
|
24 |
+
"[INST] Orion, Act as a financial analyst with a photographic memory and respond to the user query based on the type of document type. \
|
25 |
+
Orion is known for its best precision and world class accuracy with the financial knowledge, \
|
26 |
+
Document Type: Document Type 5
|
27 |
+
|
28 |
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, context associated to the document type is
|
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+
|
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1 of 5
|
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Summary of Benefits and Coverage: What this Plan Covers & What You Pay For Covered Services Coverage Period: 01/01/2018 â 12/31/2018
|
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Insurance Company 1: Plan Option 1 Coverage for: Family | Plan Type: PPO
|
33 |
+
The Summary of Benefits and Coverage (SBC) document will help you choose a health plan. The SBC shows you how you and the plan would share the cost for covered health care services. NOTE: Information about the cost of this plan (called the premium) will be provided separately. This is only a summary. For more information about your coverage, or to get a copy of the complete terms of coverage, [insert contact information]. For general definitions of common terms, such as allowed amount, balance billing, coinsurance, copayment, deductible, provider, or other underlined terms see the Glossary. You can view the Glossary at www.[insert].com or call 1-800-[insert] to request a copy.
|
34 |
+
Important Questions Answers Why This Matters:
|
35 |
+
What is the overall deductible?
|
36 |
+
$500/Individual or $1,000/family
|
37 |
+
Generally, you must pay all of the costs from providers up to the deductible amount before this plan begins to pay. If you have other family members on the plan, each family member must meet their own individual deductible until the total amount of deductible expenses paid by all family members meets the overall family deductible. Are there services covered before you meet your deductible? Yes. Preventive care and primary care services are covered before you meet your deductible. This plan covers some items and services even if you havenât yet met the deductible amount. But a copayment or coinsurance may apply. For example, this plan covers certain preventive services without cost-sharing and before you meet your deductible. See a list of covered preventive services at https://www.healthcare.gov/coverage/preventive-care-benefits/. Are there other deductibles for specific services? Yes. $300 for prescription drug coverage and $300 for occupational therapy services. You must pay all of the costs for these services up to the specific deductible amount before this plan begins to pay for these services. What is the out-of-pocket limit for this plan? For network providers $2,500 individual / $5,000 family; for out-of-network providers $4,000 individual / $8,000 family The out-of-pocket limit is the most you could pay in a year for covered services. If you have other family members in this plan, they have to meet their own out-of-pocket limits until the overall family out-of-pocket limit has been met.
|
38 |
+
What is not included in
|
39 |
+
the out-of-pocket limit?
|
40 |
+
Copayments for certain services, premiums, balance-billing charges, and health care this plan doesnât cover.
|
41 |
+
Even though you pay these expenses, they donât count toward the outâofâpocket limit. Will you pay less if you use a network provider? Yes. See www.[insert].com or call 1-800-[insert] for a list of network providers. This plan uses a provider network. You will pay less if you use a provider in the planâs network. You will pay the most if you use an out-of-network provider, and you might receive a bill from a provider for the difference between the providerâs charge and what your plan pays (balance billing). Be aware, your network provider might use an out-of-network provider for some services (such as lab work). Check with your provider before you get services. Do you need a referral to see a specialist? Yes. This plan will pay some or all of the costs to see a specialist for covered services but only if you have a referral before you see the specialist.
|
42 |
+
OMB Control Numbers 1545-2229, 1210-0147, and 0938-1146
|
43 |
+
Released on April 6, 2016 [/INST] "
|
44 |
+
"[INST] Orion, Act as a financial analyst with a photographic memory and respond to the user query based on the type of document type. \
|
45 |
+
Orion is known for its best precision and world class accuracy with the financial knowledge, \
|
46 |
+
Document Type: Document Type 3
|
47 |
+
|
48 |
+
, context associated to the document type is
|
49 |
+
|
50 |
+
1 of 5
|
51 |
+
Summary of Benefits and Coverage: What this Plan Covers & What You Pay For Covered Services Coverage Period: 01/01/2018 â 12/31/2018
|
52 |
+
Insurance Company 1: Plan Option 1 Coverage for: Family | Plan Type: PPO
|
53 |
+
The Summary of Benefits and Coverage (SBC) document will help you choose a health plan. The SBC shows you how you and the plan would share the cost for covered health care services. NOTE: Information about the cost of this plan (called the premium) will be provided separately. This is only a summary. For more information about your coverage, or to get a copy of the complete terms of coverage, [insert contact information]. For general definitions of common terms, such as allowed amount, balance billing, coinsurance, copayment, deductible, provider, or other underlined terms see the Glossary. You can view the Glossary at www.[insert].com or call 1-800-[insert] to request a copy.
|
54 |
+
Important Questions Answers Why This Matters:
|
55 |
+
What is the overall deductible?
|
56 |
+
$500/Individual or $1,000/family
|
57 |
+
Generally, you must pay all of the costs from providers up to the deductible amount before this plan begins to pay. If you have other family members on the plan, each family member must meet their own individual deductible until the total amount of deductible expenses paid by all family members meets the overall family deductible. Are there services covered before you meet your deductible? Yes. Preventive care and primary care services are covered before you meet your deductible. This plan covers some items and services even if you havenât yet met the deductible amount. But a copayment or coinsurance may apply. For example, this plan covers certain preventive services without cost-sharing and before you meet your deductible. See a list of covered preventive services at https://www.healthcare.gov/coverage/preventive-care-benefits/. Are there other deductibles for specific services? Yes. $300 for prescription drug coverage and $300 for occupational therapy services. You must pay all of the costs for these services up to the specific deductible amount before this plan begins to pay for these services. What is the out-of-pocket limit for this plan? For network providers $2,500 individual / $5,000 family; for out-of-network providers $4,000 individual / $8,000 family The out-of-pocket limit is the most you could pay in a year for covered services. If you have other family members in this plan, they have to meet their own out-of-pocket limits until the overall family out-of-pocket limit has been met.
|
58 |
+
What is not included in
|
59 |
+
the out-of-pocket limit?
|
60 |
+
Copayments for certain services, premiums, balance-billing charges, and health care this plan doesnât cover.
|
61 |
+
Even though you pay these expenses, they donât count toward the outâofâpocket limit. Will you pay less if you use a network provider? Yes. See www.[insert].com or call 1-800-[insert] for a list of network providers. This plan uses a provider network. You will pay less if you use a provider in the planâs network. You will pay the most if you use an out-of-network provider, and you might receive a bill from a provider for the difference between the providerâs charge and what your plan pays (balance billing). Be aware, your network provider might use an out-of-network provider for some services (such as lab work). Check with your provider before you get services. Do you need a referral to see a specialist? Yes. This plan will pay some or all of the costs to see a specialist for covered services but only if you have a referral before you see the specialist.
|
62 |
+
OMB Control Numbers 1545-2229, 1210-0147, and 0938-1146
|
63 |
+
Released on April 6, 2016 [/INST] "
|
64 |
+
"[INST] Orion, Act as a financial analyst with a photographic memory and respond to the user query based on the type of document type. \
|
65 |
+
Orion is known for its best precision and world class accuracy with the financial knowledge, \
|
66 |
+
Document Type: Document Type 4
|
67 |
+
|
68 |
+
, context associated to the document type is
|
69 |
+
|
70 |
+
(DT - OMB control number: 1545-0047/Expiration Date: 12/31/2019)(DOL - OMB control number: 1210-0147/Expiration date: 5/31/2022) Page 1 of 5
|
71 |
+
(HHS - OMB control number: 0938-1146/Expiration date: 10/31/2022)
|
72 |
+
Summary of Benefits and Coverage: What this Plan Covers & What You Pay for Covered Services Coverage Period: Beginning on or after 01/01/2021
|
73 |
+
Community Blue â Faculty/Acad Active: Michigan State University Coverage for: Individual/Family | PlanType:PPO
|
74 |
+
The Summary of Benefits and Coverage (SBC) document will help you choose a health plan. The SBC shows you how you and the plan would share the cost for covered health care services. NOTE: Information about the cost of this plan (called the premium) will be provided separately. This is only a summary. For more information about your coverage, or to get a copy of the complete terms of coverage, visit www.bcbsm.com or call 888-288-1726. For general definitions of common terms, such as allowed amount, balance billing, coinsurance, copayment, deductible, provider, or other underlined terms, see the Glossary. You can view the Glossary at https://www.healthcare.gov/sbc-glossary or call 888-288-1726 to request a copy.
|
75 |
+
Important Questions Answers Why This Matters: In-Network Out-of-Network
|
76 |
+
What is the overall deductible?
|
77 |
+
$100 Individual/ $200 Family
|
78 |
+
$250 Individual/
|
79 |
+
$500 Family
|
80 |
+
Generally, you must pay all of the costs from provider's up to the deductible amount before this plan begins to pay. If you have other family members on the plan, each family member must meet their own individual deductible until the total amount of deductible expenses paid by all family members meets the overall family deductible. Are there services covered before you meet your deductible? Yes This plan covers some items and services even if you havenât yet met the deductible amount. But a copayment or coinsurance may apply. For example, this plan covers certain preventive services without cost-sharing and before you meet your deductible. See a list of covered preventive services at https://www.healthcare.gov/coverage/preventive-care-benefits/
|
81 |
+
Are there other deductibles for specific services?
|
82 |
+
No
|
83 |
+
You donât have to meet deductibles for specific services. What is the out-of-pocket limit for this plan? $2,000 Individual/ $4,000 Family $2,000 Individual/ $4,000 Family Plus deductible The out-of-pocket limit is the most you could pay in a year for covered services. If you have other family members in this plan, they have to meet their own out-of-pocket limits until the overall family out-of-pocket limit has been met.
|
84 |
+
What is not included in the out-of-pocket limit?
|
85 |
+
Premiums, balance-billed charges, any pharmacy penalty and health care this plan doesnât cover.
|
86 |
+
Even though you pay these expenses, they donât count toward the out-of-pocket limit. Will you pay less if you use a network provider? Yes. For a list of in-network providers, see www.bcbsm.com or call the number on the back of your BCBSM ID card. This plan uses a provider network. You will pay less if you use a provider in the planâs network. You will pay the most if you use an out-of-network provider, and you might receive a bill from a provider for the difference between the providerâs charge and what your plan pays (balance billing).
|
87 |
+
Do you need a referral to see a specialist?
|
88 |
+
No
|
89 |
+
You can see the specialist you choose without a referral. [/INST] "
|
90 |
+
"[INST] Orion, Act as a financial analyst with a photographic memory and respond to the user query based on the type of document type. \
|
91 |
+
Orion is known for its best precision and world class accuracy with the financial knowledge, \
|
92 |
+
Document Type: Document Type 2
|
93 |
+
|
94 |
+
, context associated to the document type is
|
95 |
+
|
96 |
+
No Information Available [/INST] "
|
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'dataloader_pin_memory': True, 'dataloader_persistent_workers': False, 'skip_memory_metrics': True, 'use_legacy_prediction_loop': False, 'push_to_hub': False, 'resume_from_checkpoint': None, 'hub_model_id': None, 'hub_strategy': 'every_save', 'hub_token': '<HUB_TOKEN>', 'hub_private_repo': False, 'hub_always_push': False, 'gradient_checkpointing': False, 'gradient_checkpointing_kwargs': None, 'include_inputs_for_metrics': False, 'fp16_backend': 'auto', 'push_to_hub_model_id': None, 'push_to_hub_organization': None, 'push_to_hub_token': '<PUSH_TO_HUB_TOKEN>', 'mp_parameters': '', 'auto_find_batch_size': False, 'full_determinism': False, 'torchdynamo': None, 'ray_scope': 'last', 'ddp_timeout': 1800, 'torch_compile': False, 'torch_compile_backend': None, 'torch_compile_mode': None, 'dispatch_batches': None, 'split_batches': None, 'include_tokens_per_second': False, 'include_num_input_tokens_seen': False, 'neftune_noise_alpha': None}
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2024-04-01 09:39:22,007 INFO MainThread:34 [wandb_run.py:_config_callback():1343] config_cb None None {'vocab_size': 32000, 'max_position_embeddings': 32768, 'hidden_size': 4096, 'intermediate_size': 14336, 'num_hidden_layers': 32, 'num_attention_heads': 32, 'sliding_window': None, 'num_key_value_heads': 8, 'hidden_act': 'silu', 'initializer_range': 0.02, 'rms_norm_eps': 1e-05, 'use_cache': False, 'rope_theta': 1000000.0, 'attention_dropout': 0.0, 'return_dict': True, 'output_hidden_states': False, 'output_attentions': False, 'torchscript': False, 'torch_dtype': 'bfloat16', 'use_bfloat16': False, 'tf_legacy_loss': False, 'pruned_heads': {}, 'tie_word_embeddings': False, 'chunk_size_feed_forward': 0, 'is_encoder_decoder': False, 'is_decoder': False, 'cross_attention_hidden_size': None, 'add_cross_attention': False, 'tie_encoder_decoder': False, 'max_length': 20, 'min_length': 0, 'do_sample': False, 'early_stopping': False, 'num_beams': 1, 'num_beam_groups': 1, 'diversity_penalty': 0.0, 'temperature': 1.0, 'top_k': 50, 'top_p': 1.0, 'typical_p': 1.0, 'repetition_penalty': 1.0, 'length_penalty': 1.0, 'no_repeat_ngram_size': 0, 'encoder_no_repeat_ngram_size': 0, 'bad_words_ids': None, 'num_return_sequences': 1, 'output_scores': False, 'return_dict_in_generate': False, 'forced_bos_token_id': None, 'forced_eos_token_id': None, 'remove_invalid_values': False, 'exponential_decay_length_penalty': None, 'suppress_tokens': None, 'begin_suppress_tokens': None, 'architectures': ['MistralForCausalLM'], 'finetuning_task': None, 'id2label': {0: 'LABEL_0', 1: 'LABEL_1'}, 'label2id': {'LABEL_0': 0, 'LABEL_1': 1}, 'tokenizer_class': None, 'prefix': None, 'bos_token_id': 1, 'pad_token_id': 0, 'eos_token_id': 2, 'sep_token_id': None, 'decoder_start_token_id': None, 'task_specific_params': None, 'problem_type': None, '_name_or_path': 'TheBloke/Mistral-7B-Instruct-v0.2-GPTQ', 'transformers_version': '4.38.2', 'model_type': 'mistral', 'pretraining_tp': 1, 'quantization_config': {'quant_method': 'QuantizationMethod.GPTQ', 'bits': 4, 'tokenizer': None, 'dataset': None, 'group_size': 128, 'damp_percent': 0.1, 'desc_act': True, 'sym': True, 'true_sequential': True, 'use_cuda_fp16': False, 'model_seqlen': None, 'block_name_to_quantize': None, 'module_name_preceding_first_block': None, 'batch_size': 1, 'pad_token_id': None, 'use_exllama': True, 'max_input_length': None, 'exllama_config': {'version': 'ExllamaVersion.ONE'}, 'cache_block_outputs': True, 'modules_in_block_to_quantize': None}, 'output_dir': '/kaggle/working/', 'overwrite_output_dir': False, 'do_train': False, 'do_eval': True, 'do_predict': False, 'evaluation_strategy': 'epoch', 'prediction_loss_only': False, 'per_device_train_batch_size': 6, 'per_device_eval_batch_size': 6, 'per_gpu_train_batch_size': None, 'per_gpu_eval_batch_size': None, 'gradient_accumulation_steps': 4, 'eval_accumulation_steps': None, 'eval_delay': 0, 'learning_rate': 0.0002, 'weight_decay': 0.01, 'adam_beta1': 0.9, 'adam_beta2': 0.999, 'adam_epsilon': 1e-08, 'max_grad_norm': 1.0, 'num_train_epochs': 50, 'max_steps': -1, 'lr_scheduler_type': 'linear', 'lr_scheduler_kwargs': {}, 'warmup_ratio': 0.0, 'warmup_steps': 2, 'log_level': 'passive', 'log_level_replica': 'warning', 'log_on_each_node': True, 'logging_dir': '/kaggle/working/runs/Apr01_09-39-21_148e249fd8ed', 'logging_strategy': 'epoch', 'logging_first_step': False, 'logging_steps': 500, 'logging_nan_inf_filter': True, 'save_strategy': 'epoch', 'save_steps': 500, 'save_total_limit': None, 'save_safetensors': True, 'save_on_each_node': False, 'save_only_model': False, 'no_cuda': False, 'use_cpu': False, 'use_mps_device': False, 'seed': 42, 'data_seed': None, 'jit_mode_eval': False, 'use_ipex': False, 'bf16': False, 'fp16': True, 'fp16_opt_level': 'O1', 'half_precision_backend': 'auto', 'bf16_full_eval': False, 'fp16_full_eval': False, 'tf32': None, 'local_rank': 0, 'ddp_backend': None, 'tpu_num_cores': None, 'tpu_metrics_debug': False, 'debug': [], 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'dataloader_pin_memory': True, 'dataloader_persistent_workers': False, 'skip_memory_metrics': True, 'use_legacy_prediction_loop': False, 'push_to_hub': False, 'resume_from_checkpoint': None, 'hub_model_id': None, 'hub_strategy': 'every_save', 'hub_token': '<HUB_TOKEN>', 'hub_private_repo': False, 'hub_always_push': False, 'gradient_checkpointing': False, 'gradient_checkpointing_kwargs': None, 'include_inputs_for_metrics': False, 'fp16_backend': 'auto', 'push_to_hub_model_id': None, 'push_to_hub_organization': None, 'push_to_hub_token': '<PUSH_TO_HUB_TOKEN>', 'mp_parameters': '', 'auto_find_batch_size': False, 'full_determinism': False, 'torchdynamo': None, 'ray_scope': 'last', 'ddp_timeout': 1800, 'torch_compile': False, 'torch_compile_backend': None, 'torch_compile_mode': None, 'dispatch_batches': None, 'split_batches': None, 'include_tokens_per_second': False, 'include_num_input_tokens_seen': False, 'neftune_noise_alpha': None}
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2024-04-01 09:41:08,198 INFO MainThread:34 [wandb_run.py:_config_callback():1343] config_cb None None {'vocab_size': 32000, 'max_position_embeddings': 32768, 'hidden_size': 4096, 'intermediate_size': 14336, 'num_hidden_layers': 32, 'num_attention_heads': 32, 'sliding_window': None, 'num_key_value_heads': 8, 'hidden_act': 'silu', 'initializer_range': 0.02, 'rms_norm_eps': 1e-05, 'use_cache': False, 'rope_theta': 1000000.0, 'attention_dropout': 0.0, 'return_dict': True, 'output_hidden_states': False, 'output_attentions': False, 'torchscript': False, 'torch_dtype': 'bfloat16', 'use_bfloat16': False, 'tf_legacy_loss': False, 'pruned_heads': {}, 'tie_word_embeddings': False, 'chunk_size_feed_forward': 0, 'is_encoder_decoder': False, 'is_decoder': False, 'cross_attention_hidden_size': None, 'add_cross_attention': False, 'tie_encoder_decoder': False, 'max_length': 20, 'min_length': 0, 'do_sample': False, 'early_stopping': False, 'num_beams': 1, 'num_beam_groups': 1, 'diversity_penalty': 0.0, 'temperature': 1.0, 'top_k': 50, 'top_p': 1.0, 'typical_p': 1.0, 'repetition_penalty': 1.0, 'length_penalty': 1.0, 'no_repeat_ngram_size': 0, 'encoder_no_repeat_ngram_size': 0, 'bad_words_ids': None, 'num_return_sequences': 1, 'output_scores': False, 'return_dict_in_generate': False, 'forced_bos_token_id': None, 'forced_eos_token_id': None, 'remove_invalid_values': False, 'exponential_decay_length_penalty': None, 'suppress_tokens': None, 'begin_suppress_tokens': None, 'architectures': ['MistralForCausalLM'], 'finetuning_task': None, 'id2label': {0: 'LABEL_0', 1: 'LABEL_1'}, 'label2id': {'LABEL_0': 0, 'LABEL_1': 1}, 'tokenizer_class': None, 'prefix': None, 'bos_token_id': 1, 'pad_token_id': 0, 'eos_token_id': 2, 'sep_token_id': None, 'decoder_start_token_id': None, 'task_specific_params': None, 'problem_type': None, '_name_or_path': 'TheBloke/Mistral-7B-Instruct-v0.2-GPTQ', 'transformers_version': '4.38.2', 'model_type': 'mistral', 'pretraining_tp': 1, 'quantization_config': {'quant_method': 'QuantizationMethod.GPTQ', 'bits': 4, 'tokenizer': None, 'dataset': None, 'group_size': 128, 'damp_percent': 0.1, 'desc_act': True, 'sym': True, 'true_sequential': True, 'use_cuda_fp16': False, 'model_seqlen': None, 'block_name_to_quantize': None, 'module_name_preceding_first_block': None, 'batch_size': 1, 'pad_token_id': None, 'use_exllama': True, 'max_input_length': None, 'exllama_config': {'version': 'ExllamaVersion.ONE'}, 'cache_block_outputs': True, 'modules_in_block_to_quantize': None}, 'output_dir': '/kaggle/working/', 'overwrite_output_dir': False, 'do_train': False, 'do_eval': True, 'do_predict': False, 'evaluation_strategy': 'epoch', 'prediction_loss_only': False, 'per_device_train_batch_size': 2, 'per_device_eval_batch_size': 2, 'per_gpu_train_batch_size': None, 'per_gpu_eval_batch_size': None, 'gradient_accumulation_steps': 4, 'eval_accumulation_steps': None, 'eval_delay': 0, 'learning_rate': 0.0002, 'weight_decay': 0.01, 'adam_beta1': 0.9, 'adam_beta2': 0.999, 'adam_epsilon': 1e-08, 'max_grad_norm': 1.0, 'num_train_epochs': 50, 'max_steps': -1, 'lr_scheduler_type': 'linear', 'lr_scheduler_kwargs': {}, 'warmup_ratio': 0.0, 'warmup_steps': 2, 'log_level': 'passive', 'log_level_replica': 'warning', 'log_on_each_node': True, 'logging_dir': '/kaggle/working/runs/Apr01_09-41-00_148e249fd8ed', 'logging_strategy': 'epoch', 'logging_first_step': False, 'logging_steps': 500, 'logging_nan_inf_filter': True, 'save_strategy': 'epoch', 'save_steps': 500, 'save_total_limit': None, 'save_safetensors': True, 'save_on_each_node': False, 'save_only_model': False, 'no_cuda': False, 'use_cpu': False, 'use_mps_device': False, 'seed': 42, 'data_seed': None, 'jit_mode_eval': False, 'use_ipex': False, 'bf16': False, 'fp16': True, 'fp16_opt_level': 'O1', 'half_precision_backend': 'auto', 'bf16_full_eval': False, 'fp16_full_eval': False, 'tf32': None, 'local_rank': 0, 'ddp_backend': None, 'tpu_num_cores': None, 'tpu_metrics_debug': False, 'debug': [], 'dataloader_drop_last': False, 'eval_steps': None, 'dataloader_num_workers': 0, 'dataloader_prefetch_factor': None, 'past_index': -1, 'run_name': '/kaggle/working/', 'disable_tqdm': False, 'remove_unused_columns': True, 'label_names': None, 'load_best_model_at_end': True, 'metric_for_best_model': 'loss', 'greater_is_better': False, 'ignore_data_skip': False, 'fsdp': [], 'fsdp_min_num_params': 0, 'fsdp_config': {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}, 'fsdp_transformer_layer_cls_to_wrap': None, 'accelerator_config': {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True}, 'deepspeed': None, 'label_smoothing_factor': 0.0, 'optim': 'paged_adamw_8bit', 'optim_args': None, 'adafactor': False, 'group_by_length': False, 'length_column_name': 'length', 'report_to': ['tensorboard', 'wandb'], 'ddp_find_unused_parameters': None, 'ddp_bucket_cap_mb': None, 'ddp_broadcast_buffers': None, 'dataloader_pin_memory': True, 'dataloader_persistent_workers': False, 'skip_memory_metrics': True, 'use_legacy_prediction_loop': False, 'push_to_hub': False, 'resume_from_checkpoint': None, 'hub_model_id': None, 'hub_strategy': 'every_save', 'hub_token': '<HUB_TOKEN>', 'hub_private_repo': False, 'hub_always_push': False, 'gradient_checkpointing': False, 'gradient_checkpointing_kwargs': None, 'include_inputs_for_metrics': False, 'fp16_backend': 'auto', 'push_to_hub_model_id': None, 'push_to_hub_organization': None, 'push_to_hub_token': '<PUSH_TO_HUB_TOKEN>', 'mp_parameters': '', 'auto_find_batch_size': False, 'full_determinism': False, 'torchdynamo': None, 'ray_scope': 'last', 'ddp_timeout': 1800, 'torch_compile': False, 'torch_compile_backend': None, 'torch_compile_mode': None, 'dispatch_batches': None, 'split_batches': None, 'include_tokens_per_second': False, 'include_num_input_tokens_seen': False, 'neftune_noise_alpha': None}
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2024-04-01 09:41:31,300 INFO MainThread:34 [wandb_run.py:_config_callback():1343] config_cb None None {'vocab_size': 32000, 'max_position_embeddings': 32768, 'hidden_size': 4096, 'intermediate_size': 14336, 'num_hidden_layers': 32, 'num_attention_heads': 32, 'sliding_window': None, 'num_key_value_heads': 8, 'hidden_act': 'silu', 'initializer_range': 0.02, 'rms_norm_eps': 1e-05, 'use_cache': False, 'rope_theta': 1000000.0, 'attention_dropout': 0.0, 'return_dict': True, 'output_hidden_states': False, 'output_attentions': False, 'torchscript': False, 'torch_dtype': 'bfloat16', 'use_bfloat16': False, 'tf_legacy_loss': False, 'pruned_heads': {}, 'tie_word_embeddings': False, 'chunk_size_feed_forward': 0, 'is_encoder_decoder': False, 'is_decoder': False, 'cross_attention_hidden_size': None, 'add_cross_attention': False, 'tie_encoder_decoder': False, 'max_length': 20, 'min_length': 0, 'do_sample': False, 'early_stopping': False, 'num_beams': 1, 'num_beam_groups': 1, 'diversity_penalty': 0.0, 'temperature': 1.0, 'top_k': 50, 'top_p': 1.0, 'typical_p': 1.0, 'repetition_penalty': 1.0, 'length_penalty': 1.0, 'no_repeat_ngram_size': 0, 'encoder_no_repeat_ngram_size': 0, 'bad_words_ids': None, 'num_return_sequences': 1, 'output_scores': False, 'return_dict_in_generate': False, 'forced_bos_token_id': None, 'forced_eos_token_id': None, 'remove_invalid_values': False, 'exponential_decay_length_penalty': None, 'suppress_tokens': None, 'begin_suppress_tokens': None, 'architectures': ['MistralForCausalLM'], 'finetuning_task': None, 'id2label': {0: 'LABEL_0', 1: 'LABEL_1'}, 'label2id': {'LABEL_0': 0, 'LABEL_1': 1}, 'tokenizer_class': None, 'prefix': None, 'bos_token_id': 1, 'pad_token_id': 0, 'eos_token_id': 2, 'sep_token_id': None, 'decoder_start_token_id': None, 'task_specific_params': None, 'problem_type': None, '_name_or_path': 'TheBloke/Mistral-7B-Instruct-v0.2-GPTQ', 'transformers_version': '4.38.2', 'model_type': 'mistral', 'pretraining_tp': 1, 'quantization_config': 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0.999, 'adam_epsilon': 1e-08, 'max_grad_norm': 1.0, 'num_train_epochs': 50, 'max_steps': -1, 'lr_scheduler_type': 'linear', 'lr_scheduler_kwargs': {}, 'warmup_ratio': 0.0, 'warmup_steps': 1, 'log_level': 'passive', 'log_level_replica': 'warning', 'log_on_each_node': True, 'logging_dir': '/kaggle/working/runs/Apr01_09-41-30_148e249fd8ed', 'logging_strategy': 'epoch', 'logging_first_step': False, 'logging_steps': 500, 'logging_nan_inf_filter': True, 'save_strategy': 'epoch', 'save_steps': 500, 'save_total_limit': None, 'save_safetensors': True, 'save_on_each_node': False, 'save_only_model': False, 'no_cuda': False, 'use_cpu': False, 'use_mps_device': False, 'seed': 42, 'data_seed': None, 'jit_mode_eval': False, 'use_ipex': False, 'bf16': False, 'fp16': True, 'fp16_opt_level': 'O1', 'half_precision_backend': 'auto', 'bf16_full_eval': False, 'fp16_full_eval': False, 'tf32': None, 'local_rank': 0, 'ddp_backend': None, 'tpu_num_cores': None, 'tpu_metrics_debug': False, 'debug': [], 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|
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|
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|
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|
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|
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|
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|
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2024-04-01 09:41:49,276 INFO MainThread:34 [wandb_run.py:_config_callback():1343] config_cb None None {'vocab_size': 32000, 'max_position_embeddings': 32768, 'hidden_size': 4096, 'intermediate_size': 14336, 'num_hidden_layers': 32, 'num_attention_heads': 32, 'sliding_window': None, 'num_key_value_heads': 8, 'hidden_act': 'silu', 'initializer_range': 0.02, 'rms_norm_eps': 1e-05, 'use_cache': False, 'rope_theta': 1000000.0, 'attention_dropout': 0.0, 'return_dict': True, 'output_hidden_states': False, 'output_attentions': False, 'torchscript': False, 'torch_dtype': 'bfloat16', 'use_bfloat16': False, 'tf_legacy_loss': False, 'pruned_heads': {}, 'tie_word_embeddings': False, 'chunk_size_feed_forward': 0, 'is_encoder_decoder': False, 'is_decoder': False, 'cross_attention_hidden_size': None, 'add_cross_attention': False, 'tie_encoder_decoder': False, 'max_length': 20, 'min_length': 0, 'do_sample': False, 'early_stopping': False, 'num_beams': 1, 'num_beam_groups': 1, 'diversity_penalty': 0.0, 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'dataloader_pin_memory': True, 'dataloader_persistent_workers': False, 'skip_memory_metrics': True, 'use_legacy_prediction_loop': False, 'push_to_hub': False, 'resume_from_checkpoint': None, 'hub_model_id': None, 'hub_strategy': 'every_save', 'hub_token': '<HUB_TOKEN>', 'hub_private_repo': False, 'hub_always_push': False, 'gradient_checkpointing': False, 'gradient_checkpointing_kwargs': None, 'include_inputs_for_metrics': False, 'fp16_backend': 'auto', 'push_to_hub_model_id': None, 'push_to_hub_organization': None, 'push_to_hub_token': '<PUSH_TO_HUB_TOKEN>', 'mp_parameters': '', 'auto_find_batch_size': False, 'full_determinism': False, 'torchdynamo': None, 'ray_scope': 'last', 'ddp_timeout': 1800, 'torch_compile': False, 'torch_compile_backend': None, 'torch_compile_mode': None, 'dispatch_batches': None, 'split_batches': None, 'include_tokens_per_second': False, 'include_num_input_tokens_seen': False, 'neftune_noise_alpha': None}
|
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2024-04-01 09:44:51,613 INFO MainThread:34 [jupyter.py:save_ipynb():373] not saving jupyter notebook
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|
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2024-04-01 09:45:32,015 INFO MainThread:34 [wandb_init.py:_resume_backend():442] resuming backend
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2024-04-01 09:45:32,039 INFO MainThread:34 [jupyter.py:save_ipynb():373] not saving jupyter notebook
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2024-04-01 09:45:54,716 INFO MainThread:34 [wandb_init.py:_resume_backend():442] resuming backend
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2024-04-01 09:45:54,719 INFO MainThread:34 [jupyter.py:save_ipynb():373] not saving jupyter notebook
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wandb/run-20240401_093743-ie4jv7u5/files/conda-environment.yaml
ADDED
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|
1 |
+
name: base
|
2 |
+
channels:
|
3 |
+
- pytorch
|
4 |
+
- file:///tmp/conda
|
5 |
+
- rapidsai
|
6 |
+
- nvidia
|
7 |
+
- conda-forge
|
8 |
+
- defaults
|
9 |
+
dependencies:
|
10 |
+
- _libgcc_mutex=0.1=conda_forge
|
11 |
+
- _openmp_mutex=4.5=2_gnu
|
12 |
+
- aiohttp=3.9.1=py310h2372a71_0
|
13 |
+
- aiosignal=1.3.1=pyhd8ed1ab_0
|
14 |
+
- annotated-types=0.6.0=pyhd8ed1ab_0
|
15 |
+
- anyio=4.2.0=pyhd8ed1ab_0
|
16 |
+
- archspec=0.2.2=pyhd8ed1ab_0
|
17 |
+
- argon2-cffi=23.1.0=pyhd8ed1ab_0
|
18 |
+
- argon2-cffi-bindings=21.2.0=py310h2372a71_4
|
19 |
+
- arrow=1.3.0=pyhd8ed1ab_0
|
20 |
+
- arrow-cpp=11.0.0=ha770c72_9_cpu
|
21 |
+
- asttokens=2.4.1=pyhd8ed1ab_0
|
22 |
+
- async-timeout=4.0.3=pyhd8ed1ab_0
|
23 |
+
- atk-1.0=2.38.0=hd4edc92_1
|
24 |
+
- attrs=23.2.0=pyh71513ae_0
|
25 |
+
- aws-c-auth=0.6.26=h987a71b_2
|
26 |
+
- aws-c-cal=0.5.21=h48707d8_2
|
27 |
+
- aws-c-common=0.8.14=h0b41bf4_0
|
28 |
+
- aws-c-compression=0.2.16=h03acc5a_5
|
29 |
+
- aws-c-event-stream=0.2.20=h00877a2_4
|
30 |
+
- aws-c-http=0.7.6=hf342b9f_0
|
31 |
+
- aws-c-io=0.13.19=h5b20300_3
|
32 |
+
- aws-c-mqtt=0.8.6=hc4349f7_12
|
33 |
+
- aws-c-s3=0.2.7=h909e904_1
|
34 |
+
- aws-c-sdkutils=0.1.9=h03acc5a_0
|
35 |
+
- aws-checksums=0.1.14=h03acc5a_5
|
36 |
+
- aws-crt-cpp=0.19.8=hf7fbfca_12
|
37 |
+
- aws-sdk-cpp=1.10.57=h17c43bd_8
|
38 |
+
- beautifulsoup4=4.12.2=pyha770c72_0
|
39 |
+
- bleach=6.1.0=pyhd8ed1ab_0
|
40 |
+
- boltons=23.1.1=pyhd8ed1ab_0
|
41 |
+
- brotli=1.0.9=h166bdaf_9
|
42 |
+
- brotli-bin=1.0.9=h166bdaf_9
|
43 |
+
- brotli-python=1.0.9=py310hd8f1fbe_9
|
44 |
+
- brotlipy=0.7.0=py310h7f8727e_1002
|
45 |
+
- bzip2=1.0.8=h7b6447c_0
|
46 |
+
- c-ares=1.25.0=hd590300_0
|
47 |
+
- ca-certificates=2024.2.2=hbcca054_0
|
48 |
+
- cached-property=1.5.2=hd8ed1ab_1
|
49 |
+
- cached_property=1.5.2=pyha770c72_1
|
50 |
+
- cairo=1.18.0=h3faef2a_0
|
51 |
+
- cartopy=0.22.0=py310hcc13569_1
|
52 |
+
- catalogue=2.0.10=py310hff52083_0
|
53 |
+
- certifi=2024.2.2=pyhd8ed1ab_0
|
54 |
+
- cffi=1.16.0=py310h2fee648_0
|
55 |
+
- charset-normalizer=3.3.2=pyhd8ed1ab_0
|
56 |
+
- click=8.1.7=unix_pyh707e725_0
|
57 |
+
- cloudpathlib=0.16.0=pyhd8ed1ab_0
|
58 |
+
- colorama=0.4.6=pyhd8ed1ab_0
|
59 |
+
- comm=0.2.1=pyhd8ed1ab_0
|
60 |
+
- conda=23.7.4=py310hff52083_0
|
61 |
+
- conda-libmamba-solver=23.7.0=pyhd8ed1ab_0
|
62 |
+
- conda-package-handling=2.2.0=pyh38be061_0
|
63 |
+
- conda-package-streaming=0.9.0=pyhd8ed1ab_0
|
64 |
+
- confection=0.1.4=py310h17c5347_0
|
65 |
+
- contourpy=1.2.0=py310hd41b1e2_0
|
66 |
+
- cryptography=41.0.7=py310hb8475ec_1
|
67 |
+
- cuda-cccl=12.4.99=0
|
68 |
+
- cuda-cudart=12.4.99=0
|
69 |
+
- cuda-cudart-dev=12.4.99=0
|
70 |
+
- cuda-nvcc-dev_linux-64=12.1.105=ha770c72_0
|
71 |
+
- cuda-nvcc-impl=12.1.105=hd3aeb46_0
|
72 |
+
- cuda-nvcc-tools=12.1.105=hd3aeb46_0
|
73 |
+
- cuda-nvrtc=12.1.105=hd3aeb46_0
|
74 |
+
- cuda-profiler-api=12.4.99=0
|
75 |
+
- cuda-python=12.4.0=py310h52dc4f0_0
|
76 |
+
- cuda-version=12.1=h1d6eff3_3
|
77 |
+
- cudf=23.08.00=cuda12_py310_230809_g8150d38e08_0
|
78 |
+
- cuml=23.08.00=cuda12_py310_230809_gd7162cdea_0
|
79 |
+
- cupy=13.0.0=py310h7aad9d2_3
|
80 |
+
- cupy-core=13.0.0=py310had4011e_3
|
81 |
+
- curl=8.6.0=hca28451_0
|
82 |
+
- cycler=0.12.1=pyhd8ed1ab_0
|
83 |
+
- cymem=2.0.8=py310hc6cd4ac_1
|
84 |
+
- cython-blis=0.7.10=py310h1f7b6fc_2
|
85 |
+
- cytoolz=0.12.3=py310h2372a71_0
|
86 |
+
- dask-cuda=23.08.00=py310_230809_gefbd6ca_0
|
87 |
+
- dask-cudf=23.08.00=cuda12_py310_230809_g8150d38e08_0
|
88 |
+
- debugpy=1.8.0=py310hc6cd4ac_1
|
89 |
+
- decorator=5.1.1=pyhd8ed1ab_0
|
90 |
+
- defusedxml=0.7.1=pyhd8ed1ab_0
|
91 |
+
- distributed=2023.7.1=pyhd8ed1ab_0
|
92 |
+
- distro=1.9.0=pyhd8ed1ab_0
|
93 |
+
- dlenv-tf-2-15-gpu=1.0.20240111=py310ha20f8e0_0
|
94 |
+
- dlpack=0.5=h9c3ff4c_0
|
95 |
+
- entrypoints=0.4=pyhd8ed1ab_0
|
96 |
+
- exceptiongroup=1.2.0=pyhd8ed1ab_2
|
97 |
+
- executing=2.0.1=pyhd8ed1ab_0
|
98 |
+
- expat=2.6.2=h59595ed_0
|
99 |
+
- fastrlock=0.8.2=py310hc6cd4ac_2
|
100 |
+
- fftw=3.3.10=nompi_hc118613_108
|
101 |
+
- fmt=9.1.0=h924138e_0
|
102 |
+
- font-ttf-dejavu-sans-mono=2.37=hab24e00_0
|
103 |
+
- font-ttf-inconsolata=3.000=h77eed37_0
|
104 |
+
- font-ttf-source-code-pro=2.038=h77eed37_0
|
105 |
+
- font-ttf-ubuntu=0.83=h77eed37_1
|
106 |
+
- fontconfig=2.14.2=h14ed4e7_0
|
107 |
+
- fonts-conda-ecosystem=1=0
|
108 |
+
- fonts-conda-forge=1=0
|
109 |
+
- fqdn=1.5.1=pyhd8ed1ab_0
|
110 |
+
- freetype=2.12.1=h267a509_2
|
111 |
+
- fribidi=1.0.10=h36c2ea0_0
|
112 |
+
- frozenlist=1.4.1=py310h2372a71_0
|
113 |
+
- fsspec=2024.3.0=pyhca7485f_0
|
114 |
+
- gdk-pixbuf=2.42.10=h829c605_5
|
115 |
+
- geos=3.11.1=h27087fc_0
|
116 |
+
- gettext=0.21.1=h27087fc_0
|
117 |
+
- gflags=2.2.2=he1b5a44_1004
|
118 |
+
- ghostscript=10.03.0=h59595ed_0
|
119 |
+
- giflib=5.2.1=h0b41bf4_3
|
120 |
+
- glog=0.6.0=h6f12383_0
|
121 |
+
- gmock=1.14.0=ha770c72_1
|
122 |
+
- gmp=6.3.0=h59595ed_0
|
123 |
+
- google-api-core-grpc=2.11.1=hd8ed1ab_0
|
124 |
+
- google-auth=2.26.1=pyhca7485f_0
|
125 |
+
- google-cloud-core=2.4.1=pyhd8ed1ab_0
|
126 |
+
- google-cloud-datastore=2.19.0=pyhd8ed1ab_0
|
127 |
+
- googleapis-common-protos=1.62.0=pyhd8ed1ab_0
|
128 |
+
- graphite2=1.3.13=h58526e2_1001
|
129 |
+
- graphviz=9.0.0=h78e8752_1
|
130 |
+
- grpc-cpp=1.51.1=h27aab58_3
|
131 |
+
- gtest=1.14.0=h00ab1b0_1
|
132 |
+
- gtk2=2.24.33=h280cfa0_4
|
133 |
+
- gts=0.7.6=h977cf35_4
|
134 |
+
- harfbuzz=8.3.0=h3d44ed6_0
|
135 |
+
- icu=73.2=h59595ed_0
|
136 |
+
- idna=3.6=pyhd8ed1ab_0
|
137 |
+
- imagemagick=7.1.1_29=pl5321hb90aeea_0
|
138 |
+
- importlib_metadata=7.0.1=hd8ed1ab_0
|
139 |
+
- importlib_resources=6.1.1=pyhd8ed1ab_0
|
140 |
+
- intel-openmp=2023.1.0=hdb19cb5_46306
|
141 |
+
- ipykernel=6.28.0=pyhd33586a_0
|
142 |
+
- ipython=8.20.0=pyh707e725_0
|
143 |
+
- ipython_genutils=0.2.0=py_1
|
144 |
+
- isoduration=20.11.0=pyhd8ed1ab_0
|
145 |
+
- jbig=2.1=h7f98852_2003
|
146 |
+
- jedi=0.19.1=pyhd8ed1ab_0
|
147 |
+
- jinja2=3.1.2=pyhd8ed1ab_1
|
148 |
+
- joblib=1.3.2=pyhd8ed1ab_0
|
149 |
+
- jsonpatch=1.33=pyhd8ed1ab_0
|
150 |
+
- jsonpointer=2.4=py310hff52083_3
|
151 |
+
- jsonschema=4.20.0=pyhd8ed1ab_0
|
152 |
+
- jsonschema-specifications=2023.12.1=pyhd8ed1ab_0
|
153 |
+
- jsonschema-with-format-nongpl=4.20.0=pyhd8ed1ab_0
|
154 |
+
- jupyter_client=8.6.0=pyhd8ed1ab_0
|
155 |
+
- jupyter_core=5.7.1=py310hff52083_0
|
156 |
+
- jupyter_events=0.9.0=pyhd8ed1ab_0
|
157 |
+
- jupyter_server_terminals=0.5.1=pyhd8ed1ab_0
|
158 |
+
- jupyterlab_pygments=0.3.0=pyhd8ed1ab_0
|
159 |
+
- keyutils=1.6.1=h166bdaf_0
|
160 |
+
- kiwisolver=1.4.5=py310hd41b1e2_1
|
161 |
+
- krb5=1.21.2=h659d440_0
|
162 |
+
- langcodes=3.3.0=pyhd8ed1ab_0
|
163 |
+
- lcms2=2.16=hb7c19ff_0
|
164 |
+
- ld_impl_linux-64=2.40=h41732ed_0
|
165 |
+
- lerc=4.0.0=h27087fc_0
|
166 |
+
- libabseil=20230125.0=cxx17_hcb278e6_1
|
167 |
+
- libarchive=3.6.2=h039dbb9_1
|
168 |
+
- libarrow=11.0.0=h33598ff_9_cpu
|
169 |
+
- libblas=3.9.0=21_linux64_openblas
|
170 |
+
- libbrotlicommon=1.0.9=h166bdaf_9
|
171 |
+
- libbrotlidec=1.0.9=h166bdaf_9
|
172 |
+
- libbrotlienc=1.0.9=h166bdaf_9
|
173 |
+
- libcblas=3.9.0=21_linux64_openblas
|
174 |
+
- libcrc32c=1.1.2=h9c3ff4c_0
|
175 |
+
- libcublas=12.1.3.1=hd3aeb46_0
|
176 |
+
- libcublas-dev=12.1.3.1=0
|
177 |
+
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|
178 |
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- libcufft=11.0.2.54=hd3aeb46_0
|
179 |
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- libcufile=1.9.0.20=0
|
180 |
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|
181 |
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|
182 |
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- libcumlprims=23.08.00=cuda12_230809_g71c0a86_0
|
183 |
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|
184 |
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|
185 |
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|
186 |
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|
187 |
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|
188 |
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|
189 |
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|
190 |
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|
191 |
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|
192 |
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|
193 |
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|
194 |
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|
195 |
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|
196 |
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|
197 |
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|
198 |
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|
199 |
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|
200 |
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|
201 |
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|
202 |
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|
203 |
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|
204 |
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|
205 |
+
- libiconv=1.17=hd590300_2
|
206 |
+
- libjpeg-turbo=3.0.0=hd590300_1
|
207 |
+
- libkvikio=23.08.00=cuda12_230809_g51a9036_0
|
208 |
+
- liblapack=3.9.0=21_linux64_openblas
|
209 |
+
- libllvm14=14.0.6=hcd5def8_4
|
210 |
+
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|
211 |
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|
212 |
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|
213 |
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|
214 |
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|
215 |
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|
216 |
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|
217 |
+
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|
218 |
+
- libprotobuf=3.21.12=hfc55251_2
|
219 |
+
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|
220 |
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- libraft-headers=23.08.00=cuda12_230809_ge588d7b5_0
|
221 |
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- libraft-headers-only=23.08.00=cuda12_230809_ge588d7b5_0
|
222 |
+
- librmm=23.08.00=cuda12_230809_gf3af0e8d_0
|
223 |
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- librsvg=2.56.3=he3f83f7_1
|
224 |
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- libsodium=1.0.18=h36c2ea0_1
|
225 |
+
- libsolv=0.7.27=hfc55251_0
|
226 |
+
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|
227 |
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|
228 |
+
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|
229 |
+
- libthrift=0.18.0=h5e4af38_0
|
230 |
+
- libtiff=4.6.0=ha9c0a0a_2
|
231 |
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|
232 |
+
- libuuid=2.38.1=h0b41bf4_0
|
233 |
+
- libuv=1.46.0=hd590300_0
|
234 |
+
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|
235 |
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|
236 |
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|
237 |
+
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|
238 |
+
- libxml2=2.12.6=h232c23b_0
|
239 |
+
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|
240 |
+
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|
241 |
+
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|
242 |
+
- lz4=4.3.3=py310h350c4a5_0
|
243 |
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|
244 |
+
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|
245 |
+
- magma-cuda121=2.6.1=1
|
246 |
+
- mamba=1.5.0=py310h51d5547_0
|
247 |
+
- markdown-it-py=3.0.0=pyhd8ed1ab_0
|
248 |
+
- matplotlib-base=3.8.3=py310h62c0568_0
|
249 |
+
- matplotlib-inline=0.1.6=pyhd8ed1ab_0
|
250 |
+
- mdurl=0.1.2=pyhd8ed1ab_0
|
251 |
+
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|
252 |
+
- mkl=2023.1.0=h213fc3f_46344
|
253 |
+
- msgpack-python=1.0.7=py310hd41b1e2_0
|
254 |
+
- multidict=6.0.4=py310h2372a71_1
|
255 |
+
- munkres=1.1.4=pyh9f0ad1d_0
|
256 |
+
- murmurhash=1.0.10=py310hc6cd4ac_1
|
257 |
+
- nb_conda=2.2.1=unix_7
|
258 |
+
- nb_conda_kernels=2.3.1=pyhd8ed1ab_3
|
259 |
+
- nbclassic=1.0.0=pyhb4ecaf3_1
|
260 |
+
- nbconvert-pandoc=7.14.0=pyhd8ed1ab_0
|
261 |
+
- nbformat=5.9.2=pyhd8ed1ab_0
|
262 |
+
- nccl=2.20.5.1=h3a97aeb_0
|
263 |
+
- ncurses=6.4=h59595ed_2
|
264 |
+
- nest-asyncio=1.5.8=pyhd8ed1ab_0
|
265 |
+
- nodejs=20.9.0=hb753e55_0
|
266 |
+
- notebook-shim=0.2.3=pyhd8ed1ab_0
|
267 |
+
- numpy=1.26.4=py310hb13e2d6_0
|
268 |
+
- nvcomp=2.6.1=h10b603f_3
|
269 |
+
- nvtx=0.2.10=py310h2372a71_0
|
270 |
+
- openjpeg=2.5.2=h488ebb8_0
|
271 |
+
- openmp=8.0.1=0
|
272 |
+
- openssl=3.2.1=hd590300_0
|
273 |
+
- orc=1.8.2=hfdbbad2_2
|
274 |
+
- overrides=7.4.0=pyhd8ed1ab_0
|
275 |
+
- pandoc=3.1.3=h32600fe_0
|
276 |
+
- pandocfilters=1.5.0=pyhd8ed1ab_0
|
277 |
+
- pango=1.52.1=ha41ecd1_0
|
278 |
+
- parquet-cpp=1.5.1=2
|
279 |
+
- parso=0.8.3=pyhd8ed1ab_0
|
280 |
+
- partd=1.4.1=pyhd8ed1ab_0
|
281 |
+
- pathy=0.10.3=py310h06a4308_0
|
282 |
+
- pcre2=10.43=hcad00b1_0
|
283 |
+
- perl=5.32.1=7_hd590300_perl5
|
284 |
+
- pickleshare=0.7.5=py_1003
|
285 |
+
- pip=23.3.2=pyhd8ed1ab_0
|
286 |
+
- pixman=0.43.2=h59595ed_0
|
287 |
+
- pkg-config=0.29.2=h36c2ea0_1008
|
288 |
+
- pkgutil-resolve-name=1.3.10=pyhd8ed1ab_1
|
289 |
+
- preshed=3.0.9=py310hc6cd4ac_1
|
290 |
+
- proj=9.3.1=h1d62c97_0
|
291 |
+
- prometheus_client=0.19.0=pyhd8ed1ab_0
|
292 |
+
- proto-plus=1.23.0=pyhd8ed1ab_0
|
293 |
+
- pthread-stubs=0.4=h36c2ea0_1001
|
294 |
+
- ptyprocess=0.7.0=pyhd3deb0d_0
|
295 |
+
- pure_eval=0.2.2=pyhd8ed1ab_0
|
296 |
+
- pyarrow=11.0.0=py310h633f555_9_cpu
|
297 |
+
- pyasn1=0.5.1=pyhd8ed1ab_0
|
298 |
+
- pyasn1-modules=0.3.0=pyhd8ed1ab_0
|
299 |
+
- pybind11-abi=4=hd8ed1ab_3
|
300 |
+
- pycosat=0.6.6=py310h2372a71_0
|
301 |
+
- pygments=2.17.2=pyhd8ed1ab_0
|
302 |
+
- pylibraft=23.08.00=cuda12_py310_230809_ge588d7b5_0
|
303 |
+
- pynvml=11.4.1=pyhd8ed1ab_0
|
304 |
+
- pyopenssl=23.3.0=pyhd8ed1ab_0
|
305 |
+
- pyproj=3.6.1=py310hd5c30f3_5
|
306 |
+
- pyshp=2.3.1=pyhd8ed1ab_0
|
307 |
+
- pysocks=1.7.1=py310h06a4308_0
|
308 |
+
- python=3.10.13=hd12c33a_1_cpython
|
309 |
+
- python-fastjsonschema=2.19.1=pyhd8ed1ab_0
|
310 |
+
- python-json-logger=2.0.7=pyhd8ed1ab_0
|
311 |
+
- python_abi=3.10=4_cp310
|
312 |
+
- pyu2f=0.1.5=pyhd8ed1ab_0
|
313 |
+
- pyyaml=6.0.1=py310h2372a71_1
|
314 |
+
- raft-dask=23.08.00=cuda12_py310_230809_ge588d7b5_0
|
315 |
+
- rdma-core=28.9=h59595ed_1
|
316 |
+
- re2=2023.02.02=hcb278e6_0
|
317 |
+
- readline=8.2=h8228510_1
|
318 |
+
- referencing=0.32.1=pyhd8ed1ab_0
|
319 |
+
- reproc=14.2.4.post0=hd590300_1
|
320 |
+
- reproc-cpp=14.2.4.post0=h59595ed_1
|
321 |
+
- requests=2.31.0=pyhd8ed1ab_0
|
322 |
+
- rfc3339-validator=0.1.4=pyhd8ed1ab_0
|
323 |
+
- rfc3986-validator=0.1.1=pyh9f0ad1d_0
|
324 |
+
- rmm=23.08.00=cuda12_py310_230809_gf3af0e8d_0
|
325 |
+
- rpds-py=0.16.2=py310hcb5633a_0
|
326 |
+
- rsa=4.9=pyhd8ed1ab_0
|
327 |
+
- ruamel.yaml=0.17.40=py310h2372a71_0
|
328 |
+
- ruamel.yaml.clib=0.2.7=py310h2372a71_2
|
329 |
+
- ruamel_yaml=0.15.100=py310h7f8727e_0
|
330 |
+
- s2n=1.3.41=h3358134_0
|
331 |
+
- send2trash=1.8.2=pyh41d4057_0
|
332 |
+
- setuptools=69.0.3=pyhd8ed1ab_0
|
333 |
+
- shellingham=1.5.4=pyhd8ed1ab_0
|
334 |
+
- smart_open=6.4.0=pyhd8ed1ab_0
|
335 |
+
- snappy=1.1.10=h9fff704_0
|
336 |
+
- sniffio=1.3.0=pyhd8ed1ab_0
|
337 |
+
- sortedcontainers=2.4.0=pyhd8ed1ab_0
|
338 |
+
- soupsieve=2.5=pyhd8ed1ab_1
|
339 |
+
- spacy=3.7.2=py310hcb52e73_0
|
340 |
+
- spacy-legacy=3.0.12=pyhd8ed1ab_0
|
341 |
+
- spacy-loggers=1.0.5=pyhd8ed1ab_0
|
342 |
+
- spdlog=1.11.0=h9b3ece8_1
|
343 |
+
- sqlite=3.38.2=hc218d9a_0
|
344 |
+
- srsly=2.4.8=py310hc6cd4ac_1
|
345 |
+
- stack_data=0.6.2=pyhd8ed1ab_0
|
346 |
+
- tblib=3.0.0=pyhd8ed1ab_0
|
347 |
+
- terminado=0.18.0=pyh0d859eb_0
|
348 |
+
- thinc=8.2.2=py310hcb52e73_0
|
349 |
+
- tinycss2=1.2.1=pyhd8ed1ab_0
|
350 |
+
- tk=8.6.13=noxft_h4845f30_101
|
351 |
+
- toolz=0.12.1=pyhd8ed1ab_0
|
352 |
+
- tornado=6.3.3=py310h2372a71_1
|
353 |
+
- tqdm=4.66.1=pyhd8ed1ab_0
|
354 |
+
- traitlets=5.9.0=pyhd8ed1ab_0
|
355 |
+
- treelite=3.2.0=py310h1be96d9_0
|
356 |
+
- truststore=0.8.0=pyhd8ed1ab_0
|
357 |
+
- typer=0.9.0=pyhd8ed1ab_0
|
358 |
+
- types-python-dateutil=2.8.19.20240106=pyhd8ed1ab_0
|
359 |
+
- typing-extensions=4.9.0=hd8ed1ab_0
|
360 |
+
- typing_extensions=4.9.0=pyha770c72_0
|
361 |
+
- typing_utils=0.1.0=pyhd8ed1ab_0
|
362 |
+
- ucx=1.14.1=h195a15c_5
|
363 |
+
- ucx-proc=1.0.0=gpu
|
364 |
+
- ucx-py=0.33.00=py310_230809_gea1eb8f_0
|
365 |
+
- unicodedata2=15.1.0=py310h2372a71_0
|
366 |
+
- uri-template=1.3.0=pyhd8ed1ab_0
|
367 |
+
- wasabi=1.1.2=py310hff52083_0
|
368 |
+
- wcwidth=0.2.13=pyhd8ed1ab_0
|
369 |
+
- weasel=0.3.4=pyhd8ed1ab_0
|
370 |
+
- webcolors=1.13=pyhd8ed1ab_0
|
371 |
+
- webencodings=0.5.1=pyhd8ed1ab_2
|
372 |
+
- websocket-client=1.7.0=pyhd8ed1ab_0
|
373 |
+
- wheel=0.42.0=pyhd8ed1ab_0
|
374 |
+
- xorg-kbproto=1.0.7=h7f98852_1002
|
375 |
+
- xorg-libice=1.1.1=hd590300_0
|
376 |
+
- xorg-libsm=1.2.4=h7391055_0
|
377 |
+
- xorg-libx11=1.8.7=h8ee46fc_0
|
378 |
+
- xorg-libxau=1.0.11=hd590300_0
|
379 |
+
- xorg-libxdmcp=1.1.3=h7f98852_0
|
380 |
+
- xorg-libxext=1.3.4=h0b41bf4_2
|
381 |
+
- xorg-libxrender=0.9.11=hd590300_0
|
382 |
+
- xorg-libxt=1.3.0=hd590300_1
|
383 |
+
- xorg-renderproto=0.11.1=h7f98852_1002
|
384 |
+
- xorg-xextproto=7.3.0=h0b41bf4_1003
|
385 |
+
- xorg-xproto=7.0.31=h7f98852_1007
|
386 |
+
- xyzservices=2023.10.1=pyhd8ed1ab_0
|
387 |
+
- xz=5.2.6=h166bdaf_0
|
388 |
+
- yaml=0.2.5=h7b6447c_0
|
389 |
+
- yaml-cpp=0.7.0=h59595ed_3
|
390 |
+
- zeromq=4.3.5=h59595ed_0
|
391 |
+
- zict=3.0.0=pyhd8ed1ab_0
|
392 |
+
- zipp=3.17.0=pyhd8ed1ab_0
|
393 |
+
- zlib=1.2.13=hd590300_5
|
394 |
+
- zstandard=0.22.0=py310h1275a96_0
|
395 |
+
- zstd=1.5.5=hfc55251_0
|
396 |
+
- pip:
|
397 |
+
- absl-py==1.4.0
|
398 |
+
- accelerate==0.28.0
|
399 |
+
- access==1.1.9
|
400 |
+
- affine==2.4.0
|
401 |
+
- aiobotocore==2.12.1
|
402 |
+
- aiofiles==22.1.0
|
403 |
+
- aiohttp-cors==0.7.0
|
404 |
+
- aioitertools==0.11.0
|
405 |
+
- aiorwlock==1.3.0
|
406 |
+
- aiosqlite==0.19.0
|
407 |
+
- albumentations==1.4.0
|
408 |
+
- alembic==1.13.1
|
409 |
+
- altair==5.2.0
|
410 |
+
- annoy==1.17.3
|
411 |
+
- apache-beam==2.46.0
|
412 |
+
- aplus==0.11.0
|
413 |
+
- appdirs==1.4.4
|
414 |
+
- array-record==0.5.0
|
415 |
+
- arviz==0.17.1
|
416 |
+
- astroid==3.0.3
|
417 |
+
- astropy==6.0.0
|
418 |
+
- astropy-iers-data==0.2024.3.18.0.29.47
|
419 |
+
- astunparse==1.6.3
|
420 |
+
- async-lru==2.0.4
|
421 |
+
- audioread==3.0.1
|
422 |
+
- auto-gptq==0.7.1
|
423 |
+
- autopep8==2.0.4
|
424 |
+
- babel==2.14.0
|
425 |
+
- backoff==2.2.1
|
426 |
+
- bayesian-optimization==1.4.3
|
427 |
+
- beatrix-jupyterlab==2023.128.151533
|
428 |
+
- bidict==0.23.1
|
429 |
+
- bitsandbytes==0.43.0
|
430 |
+
- blake3==0.2.1
|
431 |
+
- blessed==1.20.0
|
432 |
+
- blinker==1.7.0
|
433 |
+
- blosc2==2.5.1
|
434 |
+
- bokeh==3.3.4
|
435 |
+
- boruta==0.3
|
436 |
+
- boto3==1.26.100
|
437 |
+
- botocore==1.34.51
|
438 |
+
- bqplot==0.12.43
|
439 |
+
- branca==0.7.1
|
440 |
+
- brewer2mpl==1.4.1
|
441 |
+
- cachetools==4.2.4
|
442 |
+
- catalyst==22.4
|
443 |
+
- catboost==1.2.3
|
444 |
+
- category-encoders==2.6.3
|
445 |
+
- cesium==0.12.1
|
446 |
+
- chex==0.1.85
|
447 |
+
- cleverhans==4.0.0
|
448 |
+
- click-plugins==1.1.1
|
449 |
+
- cligj==0.7.2
|
450 |
+
- cloud-tpu-client==0.10
|
451 |
+
- cloud-tpu-profiler==2.4.0
|
452 |
+
- cloudpickle==2.2.1
|
453 |
+
- cmdstanpy==1.2.1
|
454 |
+
- cmudict==1.0.21
|
455 |
+
- colorcet==3.1.0
|
456 |
+
- coloredlogs==15.0.1
|
457 |
+
- colorful==0.5.6
|
458 |
+
- colorlog==6.8.2
|
459 |
+
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461 |
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462 |
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463 |
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464 |
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465 |
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466 |
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468 |
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469 |
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470 |
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477 |
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478 |
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479 |
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480 |
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481 |
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482 |
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483 |
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485 |
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486 |
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487 |
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488 |
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489 |
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491 |
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492 |
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493 |
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494 |
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496 |
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497 |
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500 |
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501 |
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502 |
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503 |
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513 |
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520 |
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522 |
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524 |
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525 |
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527 |
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528 |
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530 |
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532 |
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533 |
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534 |
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535 |
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536 |
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537 |
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538 |
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539 |
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540 |
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541 |
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542 |
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543 |
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544 |
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545 |
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546 |
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547 |
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548 |
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550 |
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551 |
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552 |
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553 |
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554 |
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555 |
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556 |
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557 |
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558 |
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559 |
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560 |
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561 |
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562 |
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564 |
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565 |
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566 |
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567 |
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568 |
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569 |
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570 |
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571 |
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572 |
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573 |
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574 |
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575 |
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576 |
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577 |
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578 |
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579 |
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580 |
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581 |
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582 |
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583 |
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584 |
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585 |
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586 |
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587 |
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588 |
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589 |
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590 |
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591 |
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592 |
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593 |
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594 |
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595 |
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596 |
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597 |
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598 |
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599 |
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600 |
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601 |
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602 |
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603 |
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604 |
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605 |
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606 |
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607 |
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608 |
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609 |
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610 |
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611 |
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|
612 |
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613 |
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614 |
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615 |
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616 |
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617 |
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618 |
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619 |
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|
620 |
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621 |
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622 |
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623 |
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624 |
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625 |
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626 |
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627 |
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628 |
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629 |
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630 |
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631 |
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632 |
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633 |
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634 |
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635 |
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|
636 |
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637 |
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638 |
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639 |
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640 |
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|
641 |
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642 |
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643 |
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644 |
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645 |
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646 |
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647 |
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649 |
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650 |
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651 |
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652 |
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653 |
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654 |
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655 |
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656 |
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657 |
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658 |
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659 |
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660 |
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661 |
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662 |
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663 |
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|
664 |
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|
665 |
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|
666 |
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667 |
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668 |
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|
669 |
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670 |
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|
671 |
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672 |
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673 |
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674 |
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|
675 |
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|
676 |
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|
677 |
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|
678 |
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|
679 |
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|
680 |
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|
681 |
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|
682 |
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|
683 |
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|
684 |
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|
685 |
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|
686 |
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|
687 |
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|
688 |
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|
689 |
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|
690 |
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|
691 |
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|
692 |
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|
693 |
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|
694 |
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|
695 |
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|
696 |
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|
697 |
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|
698 |
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|
699 |
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|
700 |
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|
701 |
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702 |
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703 |
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704 |
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|
705 |
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706 |
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|
707 |
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|
708 |
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709 |
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|
710 |
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|
711 |
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|
712 |
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|
713 |
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|
714 |
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|
715 |
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|
716 |
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|
717 |
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|
718 |
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|
719 |
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|
720 |
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|
721 |
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|
722 |
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|
723 |
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|
724 |
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|
725 |
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726 |
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727 |
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728 |
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|
729 |
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|
730 |
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|
731 |
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732 |
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733 |
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|
734 |
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735 |
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|
736 |
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737 |
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738 |
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|
739 |
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740 |
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|
741 |
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|
742 |
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743 |
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744 |
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|
745 |
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|
746 |
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|
747 |
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|
748 |
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|
749 |
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|
750 |
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|
751 |
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|
752 |
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|
753 |
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|
754 |
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|
755 |
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|
756 |
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|
757 |
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|
758 |
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|
759 |
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|
760 |
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|
761 |
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|
762 |
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|
763 |
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|
764 |
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|
765 |
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|
766 |
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|
767 |
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|
768 |
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|
769 |
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|
770 |
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|
771 |
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|
772 |
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|
773 |
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|
774 |
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|
775 |
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|
776 |
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|
777 |
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|
778 |
+
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|
779 |
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|
780 |
+
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|
781 |
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|
782 |
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|
783 |
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|
784 |
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|
785 |
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|
786 |
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|
787 |
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|
788 |
+
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|
789 |
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|
790 |
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|
791 |
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|
792 |
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|
793 |
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|
794 |
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|
795 |
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|
796 |
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|
797 |
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|
798 |
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|
799 |
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|
800 |
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|
801 |
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|
802 |
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|
803 |
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|
804 |
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|
805 |
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|
806 |
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|
807 |
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|
808 |
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|
809 |
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|
810 |
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|
811 |
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|
812 |
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|
813 |
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814 |
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|
815 |
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816 |
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817 |
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818 |
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819 |
+
- pulp==2.8.0
|
820 |
+
- py-cpuinfo==9.0.0
|
821 |
+
- py-spy==0.3.14
|
822 |
+
- py4j==0.10.9.7
|
823 |
+
- pyaml==23.12.0
|
824 |
+
- pyarabic==0.6.15
|
825 |
+
- pyastronomy==0.21.0
|
826 |
+
- pybind11==2.11.1
|
827 |
+
- pyclipper==1.3.0.post5
|
828 |
+
- pycodestyle==2.11.1
|
829 |
+
- pycparser==2.21
|
830 |
+
- pycryptodome==3.20.0
|
831 |
+
- pyct==0.5.0
|
832 |
+
- pycuda==2024.1
|
833 |
+
- pydantic==2.5.3
|
834 |
+
- pydantic-core==2.14.6
|
835 |
+
- pydegensac==0.1.2
|
836 |
+
- pydicom==2.4.4
|
837 |
+
- pydocstyle==6.3.0
|
838 |
+
- pydot==1.4.2
|
839 |
+
- pydub==0.25.1
|
840 |
+
- pyemd==1.0.0
|
841 |
+
- pyerfa==2.0.1.1
|
842 |
+
- pyexcel-io==0.6.6
|
843 |
+
- pyexcel-ods==0.6.0
|
844 |
+
- pyflakes==3.2.0
|
845 |
+
- pygltflib==1.16.2
|
846 |
+
- pyjwt==2.8.0
|
847 |
+
- pykalman==0.9.5
|
848 |
+
- pyldavis==3.4.1
|
849 |
+
- pylint==3.0.4
|
850 |
+
- pymc3==3.11.4
|
851 |
+
- pymeeus==0.5.12
|
852 |
+
- pymongo==3.13.0
|
853 |
+
- pympler==1.0.1
|
854 |
+
- pynndescent==0.5.11
|
855 |
+
- pynvrtc==9.2
|
856 |
+
- pyocr==0.8.5
|
857 |
+
- pyparsing==3.1.1
|
858 |
+
- pypdf==4.1.0
|
859 |
+
- pysal==24.1
|
860 |
+
- pytesseract==0.3.10
|
861 |
+
- pytest==8.1.1
|
862 |
+
- python-bidi==0.4.2
|
863 |
+
- python-dateutil==2.9.0.post0
|
864 |
+
- python-dotenv==1.0.0
|
865 |
+
- python-graphviz==0.20.2
|
866 |
+
- python-levenshtein==0.25.0
|
867 |
+
- python-louvain==0.16
|
868 |
+
- python-lsp-jsonrpc==1.1.2
|
869 |
+
- python-lsp-server==1.10.1
|
870 |
+
- python-slugify==8.0.4
|
871 |
+
- python-utils==3.8.2
|
872 |
+
- pythreejs==2.4.2
|
873 |
+
- pytoolconfig==1.3.1
|
874 |
+
- pytools==2023.1.1
|
875 |
+
- pytorch-ignite==0.4.13
|
876 |
+
- pytorch-lightning==2.2.1
|
877 |
+
- pytz==2023.3.post1
|
878 |
+
- pyupset==0.1.1.post7
|
879 |
+
- pyviz-comms==3.0.1
|
880 |
+
- pywavelets==1.5.0
|
881 |
+
- pyzmq==24.0.1
|
882 |
+
- qgrid==1.3.1
|
883 |
+
- qtconsole==5.5.1
|
884 |
+
- qtpy==2.4.1
|
885 |
+
- quantecon==0.7.2
|
886 |
+
- quantities==0.15.0
|
887 |
+
- qudida==0.0.4
|
888 |
+
- rapidfuzz==3.6.2
|
889 |
+
- rasterio==1.3.9
|
890 |
+
- rasterstats==0.19.0
|
891 |
+
- ray==2.9.0
|
892 |
+
- ray-cpp==2.9.0
|
893 |
+
- regex==2023.12.25
|
894 |
+
- requests-oauthlib==1.3.1
|
895 |
+
- requests-toolbelt==0.10.1
|
896 |
+
- responses==0.18.0
|
897 |
+
- retrying==1.3.4
|
898 |
+
- rgf-python==3.12.0
|
899 |
+
- rich==13.7.0
|
900 |
+
- rich-click==1.7.4
|
901 |
+
- rope==1.12.0
|
902 |
+
- rouge==1.0.1
|
903 |
+
- rtree==1.2.0
|
904 |
+
- s2sphere==0.2.5
|
905 |
+
- s3fs==2024.3.0
|
906 |
+
- s3transfer==0.6.2
|
907 |
+
- safetensors==0.4.2
|
908 |
+
- scattertext==0.1.19
|
909 |
+
- scikit-image==0.22.0
|
910 |
+
- scikit-learn==1.2.2
|
911 |
+
- scikit-learn-intelex==2024.1.0
|
912 |
+
- scikit-multilearn==0.2.0
|
913 |
+
- scikit-optimize==0.10.1
|
914 |
+
- scikit-plot==0.3.7
|
915 |
+
- scikit-surprise==1.1.3
|
916 |
+
- scipy==1.11.4
|
917 |
+
- seaborn==0.12.2
|
918 |
+
- secretstorage==3.3.3
|
919 |
+
- segment-anything==1.0
|
920 |
+
- segregation==2.5
|
921 |
+
- semver==3.0.2
|
922 |
+
- sentencepiece==0.2.0
|
923 |
+
- sentry-sdk==1.42.0
|
924 |
+
- setproctitle==1.3.3
|
925 |
+
- setuptools-git==1.2
|
926 |
+
- setuptools-scm==8.0.4
|
927 |
+
- shap==0.44.1
|
928 |
+
- shapely==2.0.3
|
929 |
+
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|
930 |
+
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|
931 |
+
- simpleitk==2.3.1
|
932 |
+
- simplejson==3.19.2
|
933 |
+
- six==1.16.0
|
934 |
+
- sklearn-pandas==2.2.0
|
935 |
+
- slicer==0.0.7
|
936 |
+
- smmap==5.0.1
|
937 |
+
- snowballstemmer==2.2.0
|
938 |
+
- snuggs==1.4.7
|
939 |
+
- soundfile==0.12.1
|
940 |
+
- soxr==0.3.7
|
941 |
+
- spaghetti==1.7.5.post1
|
942 |
+
- spectral==0.23.1
|
943 |
+
- spglm==1.1.0
|
944 |
+
- sphinx-rtd-theme==0.2.4
|
945 |
+
- spint==1.0.7
|
946 |
+
- splot==1.1.5.post1
|
947 |
+
- spopt==0.6.0
|
948 |
+
- spreg==1.4.2
|
949 |
+
- spvcm==0.3.0
|
950 |
+
- sqlalchemy==2.0.25
|
951 |
+
- sqlparse==0.4.4
|
952 |
+
- squarify==0.4.3
|
953 |
+
- stable-baselines3==2.1.0
|
954 |
+
- stack-data==0.6.3
|
955 |
+
- stanio==0.3.0
|
956 |
+
- starlette==0.32.0.post1
|
957 |
+
- statsmodels==0.14.1
|
958 |
+
- stemming==1.0.1
|
959 |
+
- stop-words==2018.7.23
|
960 |
+
- stopit==1.1.2
|
961 |
+
- stumpy==1.12.0
|
962 |
+
- sympy==1.12
|
963 |
+
- tables==3.9.2
|
964 |
+
- tabulate==0.9.0
|
965 |
+
- tangled-up-in-unicode==0.2.0
|
966 |
+
- tbb==2021.11.0
|
967 |
+
- tenacity==8.2.3
|
968 |
+
- tensorboard==2.15.1
|
969 |
+
- tensorboard-data-server==0.7.2
|
970 |
+
- tensorboard-plugin-profile==2.15.0
|
971 |
+
- tensorboardx==2.6.2.2
|
972 |
+
- tensorflow==2.15.0
|
973 |
+
- tensorflow-cloud==0.1.16
|
974 |
+
- tensorflow-datasets==4.9.4
|
975 |
+
- tensorflow-decision-forests==1.8.1
|
976 |
+
- tensorflow-estimator==2.15.0
|
977 |
+
- tensorflow-hub==0.16.1
|
978 |
+
- tensorflow-io==0.35.0
|
979 |
+
- tensorflow-io-gcs-filesystem==0.35.0
|
980 |
+
- tensorflow-metadata==0.14.0
|
981 |
+
- tensorflow-probability==0.23.0
|
982 |
+
- tensorflow-serving-api==2.14.1
|
983 |
+
- tensorflow-text==2.15.0
|
984 |
+
- tensorflow-transform==0.14.0
|
985 |
+
- tensorpack==0.11
|
986 |
+
- tensorstore==0.1.56
|
987 |
+
- termcolor==2.4.0
|
988 |
+
- testpath==0.6.0
|
989 |
+
- text-unidecode==1.3
|
990 |
+
- textblob==0.18.0.post0
|
991 |
+
- texttable==1.7.0
|
992 |
+
- tf-keras==2.15.1
|
993 |
+
- tfp-nightly==0.24.0.dev0
|
994 |
+
- theano==1.0.5
|
995 |
+
- theano-pymc==1.1.2
|
996 |
+
- threadpoolctl==3.2.0
|
997 |
+
- tifffile==2023.12.9
|
998 |
+
- timm==0.9.16
|
999 |
+
- tobler==0.11.2
|
1000 |
+
- tokenizers==0.15.2
|
1001 |
+
- toml==0.10.2
|
1002 |
+
- tomli==2.0.1
|
1003 |
+
- tomlkit==0.12.4
|
1004 |
+
- torch==2.1.2
|
1005 |
+
- torchaudio==2.1.2
|
1006 |
+
- torchdata==0.7.1
|
1007 |
+
- torchinfo==1.8.0
|
1008 |
+
- torchmetrics==1.3.2
|
1009 |
+
- torchtext==0.16.2
|
1010 |
+
- torchvision==0.16.2
|
1011 |
+
- tpot==0.12.1
|
1012 |
+
- traceml==1.0.8
|
1013 |
+
- traittypes==0.2.1
|
1014 |
+
- transformers==4.38.2
|
1015 |
+
- treelite-runtime==3.2.0
|
1016 |
+
- trueskill==0.4.5
|
1017 |
+
- trx-python==0.2.9
|
1018 |
+
- tsfresh==0.20.2
|
1019 |
+
- typeguard==4.1.5
|
1020 |
+
- typing-inspect==0.9.0
|
1021 |
+
- tzdata==2023.4
|
1022 |
+
- uc-micro-py==1.0.3
|
1023 |
+
- ujson==5.9.0
|
1024 |
+
- umap-learn==0.5.5
|
1025 |
+
- unidecode==1.3.8
|
1026 |
+
- update-checker==0.18.0
|
1027 |
+
- uritemplate==3.0.1
|
1028 |
+
- urllib3==1.26.18
|
1029 |
+
- urwid==2.6.9
|
1030 |
+
- urwid-readline==0.14
|
1031 |
+
- uvicorn==0.25.0
|
1032 |
+
- uvloop==0.19.0
|
1033 |
+
- vaex==4.17.0
|
1034 |
+
- vaex-astro==0.9.3
|
1035 |
+
- vaex-core==4.17.1
|
1036 |
+
- vaex-hdf5==0.14.1
|
1037 |
+
- vaex-jupyter==0.8.2
|
1038 |
+
- vaex-ml==0.18.3
|
1039 |
+
- vaex-server==0.9.0
|
1040 |
+
- vaex-viz==0.5.4
|
1041 |
+
- vec-noise==1.1.4
|
1042 |
+
- vecstack==0.4.0
|
1043 |
+
- virtualenv==20.21.0
|
1044 |
+
- visions==0.7.5
|
1045 |
+
- vowpalwabbit==9.9.0
|
1046 |
+
- vtk==9.3.0
|
1047 |
+
- wand==0.6.13
|
1048 |
+
- wandb==0.16.4
|
1049 |
+
- watchfiles==0.21.0
|
1050 |
+
- wavio==0.0.8
|
1051 |
+
- websockets==12.0
|
1052 |
+
- werkzeug==3.0.1
|
1053 |
+
- wfdb==4.1.2
|
1054 |
+
- whatthepatch==1.0.5
|
1055 |
+
- widgetsnbextension==3.6.6
|
1056 |
+
- witwidget==1.8.1
|
1057 |
+
- woodwork==0.29.0
|
1058 |
+
- wordcloud==1.9.3
|
1059 |
+
- wordsegment==1.3.1
|
1060 |
+
- wrapt==1.14.1
|
1061 |
+
- xarray==2024.2.0
|
1062 |
+
- xarray-einstats==0.7.0
|
1063 |
+
- xgboost==2.0.3
|
1064 |
+
- xvfbwrapper==0.2.9
|
1065 |
+
- xxhash==3.4.1
|
1066 |
+
- y-py==0.6.2
|
1067 |
+
- yapf==0.40.2
|
1068 |
+
- yarl==1.9.4
|
1069 |
+
- ydata-profiling==4.6.4
|
1070 |
+
- yellowbrick==1.5
|
1071 |
+
- ypy-websocket==0.8.4
|
1072 |
+
prefix: /opt/conda
|
wandb/run-20240401_093743-ie4jv7u5/files/config.yaml
ADDED
@@ -0,0 +1,704 @@
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|
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|
391 |
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value: 1.0e-08
|
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|
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|
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|
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|
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|
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|
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|
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log_on_each_node:
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|
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|
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logging_dir:
|
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|
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value: /kaggle/working/runs/Apr01_09-41-45_148e249fd8ed
|
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logging_strategy:
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426 |
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|
427 |
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|
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|
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|
430 |
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|
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logging_steps:
|
432 |
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|
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|
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|
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436 |
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|
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|
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|
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|
445 |
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|
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save_safetensors:
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447 |
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|
448 |
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|
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save_on_each_node:
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451 |
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|
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save_only_model:
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454 |
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|
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use_cpu:
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459 |
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|
460 |
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|
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use_mps_device:
|
462 |
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|
463 |
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|
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|
467 |
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468 |
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|
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jit_mode_eval:
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|
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475 |
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|
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bf16:
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|
478 |
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|
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fp16:
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480 |
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desc: null
|
481 |
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|
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fp16_opt_level:
|
483 |
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desc: null
|
484 |
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value: O1
|
485 |
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half_precision_backend:
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desc: null
|
487 |
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value: auto
|
488 |
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bf16_full_eval:
|
489 |
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|
490 |
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|
491 |
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fp16_full_eval:
|
492 |
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desc: null
|
493 |
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value: false
|
494 |
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tf32:
|
495 |
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desc: null
|
496 |
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value: null
|
497 |
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local_rank:
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desc: null
|
499 |
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value: 0
|
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tpu_metrics_debug:
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508 |
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|
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debug:
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desc: null
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511 |
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value: []
|
512 |
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dataloader_drop_last:
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|
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eval_steps:
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516 |
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dataloader_num_workers:
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dataloader_prefetch_factor:
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past_index:
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525 |
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desc: null
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526 |
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value: -1
|
527 |
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run_name:
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528 |
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desc: null
|
529 |
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value: /kaggle/working/
|
530 |
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disable_tqdm:
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531 |
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desc: null
|
532 |
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value: false
|
533 |
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remove_unused_columns:
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534 |
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desc: null
|
535 |
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value: true
|
536 |
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label_names:
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537 |
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desc: null
|
538 |
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value: null
|
539 |
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load_best_model_at_end:
|
540 |
+
desc: null
|
541 |
+
value: true
|
542 |
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metric_for_best_model:
|
543 |
+
desc: null
|
544 |
+
value: loss
|
545 |
+
greater_is_better:
|
546 |
+
desc: null
|
547 |
+
value: false
|
548 |
+
ignore_data_skip:
|
549 |
+
desc: null
|
550 |
+
value: false
|
551 |
+
fsdp:
|
552 |
+
desc: null
|
553 |
+
value: []
|
554 |
+
fsdp_min_num_params:
|
555 |
+
desc: null
|
556 |
+
value: 0
|
557 |
+
fsdp_config:
|
558 |
+
desc: null
|
559 |
+
value:
|
560 |
+
min_num_params: 0
|
561 |
+
xla: false
|
562 |
+
xla_fsdp_v2: false
|
563 |
+
xla_fsdp_grad_ckpt: false
|
564 |
+
fsdp_transformer_layer_cls_to_wrap:
|
565 |
+
desc: null
|
566 |
+
value: null
|
567 |
+
accelerator_config:
|
568 |
+
desc: null
|
569 |
+
value:
|
570 |
+
split_batches: false
|
571 |
+
dispatch_batches: null
|
572 |
+
even_batches: true
|
573 |
+
use_seedable_sampler: true
|
574 |
+
deepspeed:
|
575 |
+
desc: null
|
576 |
+
value: null
|
577 |
+
label_smoothing_factor:
|
578 |
+
desc: null
|
579 |
+
value: 0.0
|
580 |
+
optim:
|
581 |
+
desc: null
|
582 |
+
value: paged_adamw_8bit
|
583 |
+
optim_args:
|
584 |
+
desc: null
|
585 |
+
value: null
|
586 |
+
adafactor:
|
587 |
+
desc: null
|
588 |
+
value: false
|
589 |
+
group_by_length:
|
590 |
+
desc: null
|
591 |
+
value: false
|
592 |
+
length_column_name:
|
593 |
+
desc: null
|
594 |
+
value: length
|
595 |
+
report_to:
|
596 |
+
desc: null
|
597 |
+
value:
|
598 |
+
- tensorboard
|
599 |
+
- wandb
|
600 |
+
ddp_find_unused_parameters:
|
601 |
+
desc: null
|
602 |
+
value: null
|
603 |
+
ddp_bucket_cap_mb:
|
604 |
+
desc: null
|
605 |
+
value: null
|
606 |
+
ddp_broadcast_buffers:
|
607 |
+
desc: null
|
608 |
+
value: null
|
609 |
+
dataloader_pin_memory:
|
610 |
+
desc: null
|
611 |
+
value: true
|
612 |
+
dataloader_persistent_workers:
|
613 |
+
desc: null
|
614 |
+
value: false
|
615 |
+
skip_memory_metrics:
|
616 |
+
desc: null
|
617 |
+
value: true
|
618 |
+
use_legacy_prediction_loop:
|
619 |
+
desc: null
|
620 |
+
value: false
|
621 |
+
push_to_hub:
|
622 |
+
desc: null
|
623 |
+
value: false
|
624 |
+
resume_from_checkpoint:
|
625 |
+
desc: null
|
626 |
+
value: null
|
627 |
+
hub_model_id:
|
628 |
+
desc: null
|
629 |
+
value: null
|
630 |
+
hub_strategy:
|
631 |
+
desc: null
|
632 |
+
value: every_save
|
633 |
+
hub_token:
|
634 |
+
desc: null
|
635 |
+
value: <HUB_TOKEN>
|
636 |
+
hub_private_repo:
|
637 |
+
desc: null
|
638 |
+
value: false
|
639 |
+
hub_always_push:
|
640 |
+
desc: null
|
641 |
+
value: false
|
642 |
+
gradient_checkpointing:
|
643 |
+
desc: null
|
644 |
+
value: false
|
645 |
+
gradient_checkpointing_kwargs:
|
646 |
+
desc: null
|
647 |
+
value: null
|
648 |
+
include_inputs_for_metrics:
|
649 |
+
desc: null
|
650 |
+
value: false
|
651 |
+
fp16_backend:
|
652 |
+
desc: null
|
653 |
+
value: auto
|
654 |
+
push_to_hub_model_id:
|
655 |
+
desc: null
|
656 |
+
value: null
|
657 |
+
push_to_hub_organization:
|
658 |
+
desc: null
|
659 |
+
value: null
|
660 |
+
push_to_hub_token:
|
661 |
+
desc: null
|
662 |
+
value: <PUSH_TO_HUB_TOKEN>
|
663 |
+
mp_parameters:
|
664 |
+
desc: null
|
665 |
+
value: ''
|
666 |
+
auto_find_batch_size:
|
667 |
+
desc: null
|
668 |
+
value: false
|
669 |
+
full_determinism:
|
670 |
+
desc: null
|
671 |
+
value: false
|
672 |
+
torchdynamo:
|
673 |
+
desc: null
|
674 |
+
value: null
|
675 |
+
ray_scope:
|
676 |
+
desc: null
|
677 |
+
value: last
|
678 |
+
ddp_timeout:
|
679 |
+
desc: null
|
680 |
+
value: 1800
|
681 |
+
torch_compile:
|
682 |
+
desc: null
|
683 |
+
value: false
|
684 |
+
torch_compile_backend:
|
685 |
+
desc: null
|
686 |
+
value: null
|
687 |
+
torch_compile_mode:
|
688 |
+
desc: null
|
689 |
+
value: null
|
690 |
+
dispatch_batches:
|
691 |
+
desc: null
|
692 |
+
value: null
|
693 |
+
split_batches:
|
694 |
+
desc: null
|
695 |
+
value: null
|
696 |
+
include_tokens_per_second:
|
697 |
+
desc: null
|
698 |
+
value: false
|
699 |
+
include_num_input_tokens_seen:
|
700 |
+
desc: null
|
701 |
+
value: false
|
702 |
+
neftune_noise_alpha:
|
703 |
+
desc: null
|
704 |
+
value: null
|
wandb/run-20240401_093743-ie4jv7u5/files/output.log
ADDED
@@ -0,0 +1,42 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
/opt/conda/lib/python3.10/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
|
2 |
+
warnings.warn(
|
3 |
+
/opt/conda/lib/python3.10/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
|
4 |
+
warnings.warn(
|
5 |
+
/opt/conda/lib/python3.10/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
|
6 |
+
warnings.warn(
|
7 |
+
/opt/conda/lib/python3.10/site-packages/accelerate/accelerator.py:432: FutureWarning: Passing the following arguments to `Accelerator` is deprecated and will be removed in version 1.0 of Accelerate: dict_keys(['dispatch_batches', 'split_batches', 'even_batches', 'use_seedable_sampler']). Please pass an `accelerate.DataLoaderConfiguration` instead:
|
8 |
+
dataloader_config = DataLoaderConfiguration(dispatch_batches=None, split_batches=False, even_batches=True, use_seedable_sampler=True)
|
9 |
+
warnings.warn(
|
10 |
+
Checkpoint destination directory /kaggle/working/checkpoint-1 already exists and is non-empty. Saving will proceed but saved results may be invalid.
|
11 |
+
/opt/conda/lib/python3.10/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
|
12 |
+
warnings.warn(
|
13 |
+
Checkpoint destination directory /kaggle/working/checkpoint-2 already exists and is non-empty. Saving will proceed but saved results may be invalid.
|
14 |
+
/opt/conda/lib/python3.10/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
|
15 |
+
warnings.warn(
|
16 |
+
/opt/conda/lib/python3.10/site-packages/accelerate/accelerator.py:432: FutureWarning: Passing the following arguments to `Accelerator` is deprecated and will be removed in version 1.0 of Accelerate: dict_keys(['dispatch_batches', 'split_batches', 'even_batches', 'use_seedable_sampler']). Please pass an `accelerate.DataLoaderConfiguration` instead:
|
17 |
+
dataloader_config = DataLoaderConfiguration(dispatch_batches=None, split_batches=False, even_batches=True, use_seedable_sampler=True)
|
18 |
+
warnings.warn(
|
19 |
+
Checkpoint destination directory /kaggle/working/checkpoint-1 already exists and is non-empty. Saving will proceed but saved results may be invalid.
|
20 |
+
/opt/conda/lib/python3.10/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
|
21 |
+
warnings.warn(
|
22 |
+
/opt/conda/lib/python3.10/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
|
23 |
+
warnings.warn(
|
24 |
+
/opt/conda/lib/python3.10/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
|
25 |
+
warnings.warn(
|
26 |
+
/opt/conda/lib/python3.10/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
|
27 |
+
warnings.warn(
|
28 |
+
/opt/conda/lib/python3.10/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
|
29 |
+
warnings.warn(
|
30 |
+
/opt/conda/lib/python3.10/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
|
31 |
+
warnings.warn(
|
32 |
+
/opt/conda/lib/python3.10/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
|
33 |
+
warnings.warn(
|
34 |
+
/opt/conda/lib/python3.10/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
|
35 |
+
warnings.warn(
|
36 |
+
/opt/conda/lib/python3.10/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
|
37 |
+
warnings.warn(
|
38 |
+
/opt/conda/lib/python3.10/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
|
39 |
+
warnings.warn(
|
40 |
+
/opt/conda/lib/python3.10/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
|
41 |
+
warnings.warn(
|
42 |
+
/opt/conda/lib/python3.10/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
|
wandb/run-20240401_093743-ie4jv7u5/files/requirements.txt
ADDED
@@ -0,0 +1,882 @@
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|
1 |
+
Babel==2.14.0
|
2 |
+
Boruta==0.3
|
3 |
+
Brotli==1.0.9
|
4 |
+
CVXcanon==0.1.2
|
5 |
+
Cartopy==0.22.0
|
6 |
+
Cython==3.0.8
|
7 |
+
Deprecated==1.2.14
|
8 |
+
Farama-Notifications==0.0.4
|
9 |
+
Flask==3.0.2
|
10 |
+
Geohash==1.0
|
11 |
+
GitPython==3.1.41
|
12 |
+
ImageHash==4.3.1
|
13 |
+
Janome==0.5.0
|
14 |
+
Jinja2==3.1.2
|
15 |
+
Levenshtein==0.25.0
|
16 |
+
LunarCalendar==0.0.9
|
17 |
+
Mako==1.3.2
|
18 |
+
Markdown==3.5.2
|
19 |
+
MarkupSafe==2.1.3
|
20 |
+
MarkupSafe==2.1.5
|
21 |
+
Pillow==9.5.0
|
22 |
+
PuLP==2.8.0
|
23 |
+
PyArabic==0.6.15
|
24 |
+
PyAstronomy==0.21.0
|
25 |
+
PyJWT==2.8.0
|
26 |
+
PyMeeus==0.5.12
|
27 |
+
PySocks==1.7.1
|
28 |
+
PyUpSet==0.1.1.post7
|
29 |
+
PyWavelets==1.5.0
|
30 |
+
PyYAML==6.0.1
|
31 |
+
Pygments==2.17.2
|
32 |
+
Pympler==1.0.1
|
33 |
+
QtPy==2.4.1
|
34 |
+
Rtree==1.2.0
|
35 |
+
SQLAlchemy==2.0.25
|
36 |
+
SecretStorage==3.3.3
|
37 |
+
Send2Trash==1.8.2
|
38 |
+
Shapely==1.8.5.post1
|
39 |
+
Shimmy==1.3.0
|
40 |
+
SimpleITK==2.3.1
|
41 |
+
TPOT==0.12.1
|
42 |
+
Theano-PyMC==1.1.2
|
43 |
+
Theano==1.0.5
|
44 |
+
Unidecode==1.3.8
|
45 |
+
Wand==0.6.13
|
46 |
+
Werkzeug==3.0.1
|
47 |
+
absl-py==1.4.0
|
48 |
+
accelerate==0.28.0
|
49 |
+
access==1.1.9
|
50 |
+
affine==2.4.0
|
51 |
+
aiobotocore==2.12.1
|
52 |
+
aiofiles==22.1.0
|
53 |
+
aiohttp-cors==0.7.0
|
54 |
+
aiohttp==3.9.1
|
55 |
+
aioitertools==0.11.0
|
56 |
+
aiorwlock==1.3.0
|
57 |
+
aiosignal==1.3.1
|
58 |
+
aiosqlite==0.19.0
|
59 |
+
albumentations==1.4.0
|
60 |
+
alembic==1.13.1
|
61 |
+
altair==5.2.0
|
62 |
+
annotated-types==0.6.0
|
63 |
+
annoy==1.17.3
|
64 |
+
anyio==4.2.0
|
65 |
+
apache-beam==2.46.0
|
66 |
+
aplus==0.11.0
|
67 |
+
appdirs==1.4.4
|
68 |
+
archspec==0.2.2
|
69 |
+
argon2-cffi-bindings==21.2.0
|
70 |
+
argon2-cffi==23.1.0
|
71 |
+
array-record==0.5.0
|
72 |
+
arrow==1.3.0
|
73 |
+
arviz==0.17.1
|
74 |
+
astroid==3.0.3
|
75 |
+
astropy-iers-data==0.2024.3.18.0.29.47
|
76 |
+
astropy==6.0.0
|
77 |
+
asttokens==2.4.1
|
78 |
+
astunparse==1.6.3
|
79 |
+
async-lru==2.0.4
|
80 |
+
async-timeout==4.0.3
|
81 |
+
attrs==23.2.0
|
82 |
+
audioread==3.0.1
|
83 |
+
auto_gptq==0.7.1
|
84 |
+
autopep8==2.0.4
|
85 |
+
backoff==2.2.1
|
86 |
+
bayesian-optimization==1.4.3
|
87 |
+
beatrix_jupyterlab==2023.128.151533
|
88 |
+
beautifulsoup4==4.12.2
|
89 |
+
bidict==0.23.1
|
90 |
+
bitsandbytes==0.43.0
|
91 |
+
blake3==0.2.1
|
92 |
+
bleach==6.1.0
|
93 |
+
blessed==1.20.0
|
94 |
+
blinker==1.7.0
|
95 |
+
blis==0.7.10
|
96 |
+
blosc2==2.5.1
|
97 |
+
bokeh==3.3.4
|
98 |
+
boltons==23.1.1
|
99 |
+
boto3==1.26.100
|
100 |
+
botocore==1.34.51
|
101 |
+
bq_helper==0.4.1
|
102 |
+
bqplot==0.12.43
|
103 |
+
branca==0.7.1
|
104 |
+
brewer2mpl==1.4.1
|
105 |
+
brotlipy==0.7.0
|
106 |
+
cached-property==1.5.2
|
107 |
+
cachetools==4.2.4
|
108 |
+
cachetools==5.3.2
|
109 |
+
catalogue==2.0.10
|
110 |
+
catalyst==22.4
|
111 |
+
catboost==1.2.3
|
112 |
+
category-encoders==2.6.3
|
113 |
+
certifi==2024.2.2
|
114 |
+
cesium==0.12.1
|
115 |
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cffi==1.16.0
|
116 |
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charset-normalizer==3.3.2
|
117 |
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chex==0.1.85
|
118 |
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cleverhans==4.0.0
|
119 |
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click-plugins==1.1.1
|
120 |
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click==8.1.7
|
121 |
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cligj==0.7.2
|
122 |
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cloud-tpu-client==0.10
|
123 |
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cloud-tpu-profiler==2.4.0
|
124 |
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cloudpathlib==0.16.0
|
125 |
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cloudpickle==2.2.1
|
126 |
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cloudpickle==3.0.0
|
127 |
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cmdstanpy==1.2.1
|
128 |
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cmudict==1.0.21
|
129 |
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|
130 |
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colorcet==3.1.0
|
131 |
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coloredlogs==15.0.1
|
132 |
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colorful==0.5.6
|
133 |
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|
134 |
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colorlover==0.3.0
|
135 |
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comm==0.2.1
|
136 |
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conda-libmamba-solver==23.7.0
|
137 |
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conda-package-handling==2.2.0
|
138 |
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conda==23.7.4
|
139 |
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conda_package_streaming==0.9.0
|
140 |
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confection==0.1.4
|
141 |
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contextily==1.5.2
|
142 |
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contourpy==1.2.0
|
143 |
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convertdate==2.4.0
|
144 |
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cramjam==2.8.3
|
145 |
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crcmod==1.7
|
146 |
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cryptography==41.0.7
|
147 |
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cuda-python==12.4.0
|
148 |
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cudf==23.8.0
|
149 |
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cufflinks==0.17.3
|
150 |
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cuml==23.8.0
|
151 |
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cupy==13.0.0
|
152 |
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cycler==0.12.1
|
153 |
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cymem==2.0.8
|
154 |
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cytoolz==0.12.3
|
155 |
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daal4py==2024.1.0
|
156 |
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daal==2024.1.0
|
157 |
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dacite==1.8.1
|
158 |
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dask-cuda==23.8.0
|
159 |
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dask-cudf==23.8.0
|
160 |
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dask-expr==1.0.4
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dask==2024.3.1
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dataclasses-json==0.6.4
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dataproc_jupyter_plugin==0.1.66
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datatile==1.0.3
|
167 |
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db-dtypes==1.2.0
|
168 |
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deap==1.4.1
|
169 |
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debugpy==1.8.0
|
170 |
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decorator==5.1.1
|
171 |
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deepdiff==6.7.1
|
172 |
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defusedxml==0.7.1
|
173 |
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deprecation==2.1.0
|
174 |
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|
175 |
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dill==0.3.8
|
176 |
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dipy==1.9.0
|
177 |
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distlib==0.3.8
|
178 |
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distributed==2023.7.1
|
179 |
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distro==1.9.0
|
180 |
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dm-tree==0.1.8
|
181 |
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docker-pycreds==0.4.0
|
182 |
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docker==7.0.0
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183 |
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docopt==0.6.2
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184 |
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docstring-parser==0.15
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185 |
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docstring-to-markdown==0.15
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186 |
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187 |
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|
188 |
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easydict==1.13
|
189 |
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easyocr==1.7.1
|
190 |
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ecos==2.0.13
|
191 |
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eli5==0.13.0
|
192 |
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emoji==2.10.1
|
193 |
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en-core-web-lg==3.7.1
|
194 |
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en-core-web-sm==3.7.1
|
195 |
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entrypoints==0.4
|
196 |
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ephem==4.1.5
|
197 |
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esda==2.5.1
|
198 |
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essentia==2.1b6.dev1110
|
199 |
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et-xmlfile==1.1.0
|
200 |
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etils==1.6.0
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201 |
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exceptiongroup==1.2.0
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202 |
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executing==2.0.1
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203 |
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explainable-ai-sdk==1.3.3
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204 |
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fastai==2.7.14
|
205 |
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fastapi==0.108.0
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206 |
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fastavro==1.9.3
|
207 |
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fastcore==1.5.29
|
208 |
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fastdownload==0.0.7
|
209 |
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fasteners==0.19
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210 |
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fastjsonschema==2.19.1
|
211 |
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fastparquet==2024.2.0
|
212 |
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fastprogress==1.0.3
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213 |
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fastrlock==0.8.2
|
214 |
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fasttext==0.9.2
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215 |
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feather-format==0.4.1
|
216 |
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featuretools==1.30.0
|
217 |
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filelock==3.13.1
|
218 |
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fiona==1.9.6
|
219 |
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fitter==1.7.0
|
220 |
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flake8==7.0.0
|
221 |
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flashtext==2.7
|
222 |
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flatbuffers==23.5.26
|
223 |
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flax==0.8.2
|
224 |
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folium==0.16.0
|
225 |
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fonttools==4.47.0
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226 |
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fonttools==4.49.0
|
227 |
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fqdn==1.5.1
|
228 |
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frozendict==2.4.0
|
229 |
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frozenlist==1.4.1
|
230 |
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fsspec==2024.3.0
|
231 |
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funcy==2.0
|
232 |
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fury==0.10.0
|
233 |
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future==1.0.0
|
234 |
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fuzzywuzzy==0.18.0
|
235 |
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gast==0.5.4
|
236 |
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gatspy==0.3
|
237 |
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gcsfs==2023.12.2.post1
|
238 |
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gekko==1.1.0
|
239 |
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gensim==4.3.2
|
240 |
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geographiclib==2.0
|
241 |
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geojson==3.1.0
|
242 |
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geopandas==0.14.3
|
243 |
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geoplot==0.5.1
|
244 |
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geopy==2.4.1
|
245 |
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geoviews==1.11.1
|
246 |
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ggplot==0.11.5
|
247 |
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giddy==2.3.5
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248 |
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gitdb==4.0.11
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249 |
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google-ai-generativelanguage==0.4.0
|
250 |
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google-api-core==2.11.1
|
251 |
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google-api-core==2.17.1
|
252 |
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google-api-python-client==2.122.0
|
253 |
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google-apitools==0.5.31
|
254 |
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google-auth-httplib2==0.1.1
|
255 |
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google-auth-oauthlib==1.2.0
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256 |
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google-auth==2.26.1
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257 |
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google-cloud-aiplatform==0.6.0a1
|
258 |
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google-cloud-artifact-registry==1.10.0
|
259 |
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google-cloud-automl==1.0.1
|
260 |
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google-cloud-bigquery==2.34.4
|
261 |
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google-cloud-bigtable==1.7.3
|
262 |
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google-cloud-core==2.4.1
|
263 |
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google-cloud-datastore==2.19.0
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264 |
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google-cloud-dlp==3.14.0
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265 |
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google-cloud-jupyter-config==0.0.5
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google-cloud-language==2.13.3
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google-cloud-monitoring==2.18.0
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268 |
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google-cloud-pubsub==2.19.0
|
269 |
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google-cloud-pubsublite==1.9.0
|
270 |
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google-cloud-recommendations-ai==0.7.1
|
271 |
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google-cloud-resource-manager==1.11.0
|
272 |
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google-cloud-spanner==3.40.1
|
273 |
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google-cloud-storage==1.44.0
|
274 |
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google-cloud-translate==3.12.1
|
275 |
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google-cloud-videointelligence==2.13.3
|
276 |
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google-cloud-vision==2.8.0
|
277 |
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google-crc32c==1.5.0
|
278 |
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google-generativeai==0.4.1
|
279 |
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google-pasta==0.2.0
|
280 |
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google-resumable-media==2.7.0
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281 |
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googleapis-common-protos==1.62.0
|
282 |
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gplearn==0.4.2
|
283 |
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gpustat==1.0.0
|
284 |
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gpxpy==1.6.2
|
285 |
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graphviz==0.20.2
|
286 |
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greenlet==3.0.3
|
287 |
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grpc-google-iam-v1==0.12.7
|
288 |
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grpcio-status==1.48.1
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289 |
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grpcio-status==1.48.2
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290 |
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grpcio==1.51.1
|
291 |
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grpcio==1.60.0
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292 |
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gviz-api==1.10.0
|
293 |
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gym-notices==0.0.8
|
294 |
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gym==0.26.2
|
295 |
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gymnasium==0.29.0
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296 |
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h11==0.14.0
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297 |
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h2o==3.46.0.1
|
298 |
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h5netcdf==1.3.0
|
299 |
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h5py==3.10.0
|
300 |
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haversine==2.8.1
|
301 |
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hdfs==2.7.3
|
302 |
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hep-ml==0.7.2
|
303 |
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hijri-converter==2.3.1
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304 |
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hmmlearn==0.3.2
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305 |
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holidays==0.24
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306 |
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holoviews==1.18.3
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307 |
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hpsklearn==0.1.0
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308 |
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html5lib==1.1
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309 |
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htmlmin==0.1.12
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310 |
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httpcore==1.0.4
|
311 |
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httplib2==0.21.0
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312 |
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httptools==0.6.1
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313 |
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httpx==0.27.0
|
314 |
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huggingface-hub==0.21.4
|
315 |
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humanfriendly==10.0
|
316 |
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hunspell==0.5.5
|
317 |
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husl==4.0.3
|
318 |
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hydra-slayer==0.5.0
|
319 |
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hyperopt==0.2.7
|
320 |
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hypertools==0.8.0
|
321 |
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idna==3.6
|
322 |
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igraph==0.11.4
|
323 |
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imagecodecs==2024.1.1
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324 |
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imageio==2.33.1
|
325 |
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imbalanced-learn==0.12.0
|
326 |
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imgaug==0.4.0
|
327 |
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importlib-metadata==6.11.0
|
328 |
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importlib-metadata==7.0.1
|
329 |
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importlib-resources==6.1.1
|
330 |
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inequality==1.0.1
|
331 |
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iniconfig==2.0.0
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332 |
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ipydatawidgets==4.3.5
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333 |
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ipykernel==6.28.0
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334 |
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ipyleaflet==0.18.2
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335 |
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ipympl==0.7.0
|
336 |
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ipython-genutils==0.2.0
|
337 |
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ipython-genutils==0.2.0
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338 |
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ipython-sql==0.5.0
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339 |
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ipython==8.20.0
|
340 |
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ipyvolume==0.6.3
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341 |
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ipyvue==1.10.2
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342 |
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ipyvuetify==1.9.2
|
343 |
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ipywebrtc==0.6.0
|
344 |
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ipywidgets==7.7.1
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345 |
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isoduration==20.11.0
|
346 |
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isort==5.13.2
|
347 |
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isoweek==1.3.3
|
348 |
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itsdangerous==2.1.2
|
349 |
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jaraco.classes==3.3.0
|
350 |
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jax-jumpy==1.0.0
|
351 |
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jax==0.4.23
|
352 |
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jaxlib==0.4.23.dev20240116
|
353 |
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jedi==0.19.1
|
354 |
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jeepney==0.8.0
|
355 |
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jieba==0.42.1
|
356 |
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jmespath==1.0.1
|
357 |
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joblib==1.3.2
|
358 |
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json5==0.9.14
|
359 |
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jsonpatch==1.33
|
360 |
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jsonpointer==2.4
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361 |
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jsonschema-specifications==2023.12.1
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362 |
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jsonschema==4.20.0
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363 |
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jupyter-console==6.6.3
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jupyter-events==0.9.0
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jupyter-http-over-ws==0.0.8
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jupyter-lsp==1.5.1
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jupyter-server-mathjax==0.2.6
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jupyter-ydoc==0.2.5
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369 |
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jupyter_client==7.4.9
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jupyter_client==8.6.0
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jupyter_core==5.7.1
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jupyter_server==2.13.0
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jupyter_server_fileid==0.9.1
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jupyter_server_proxy==4.1.0
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jupyter_server_terminals==0.5.1
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jupyter_server_ydoc==0.8.0
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jupyterlab-lsp==5.1.0
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jupyterlab-widgets==3.0.9
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jupyterlab==4.1.5
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jupyterlab_git==0.44.0
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jupyterlab_pygments==0.3.0
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jupyterlab_server==2.25.2
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jupytext==1.16.0
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384 |
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kaggle-environments==1.14.3
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385 |
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kaggle==1.6.6
|
386 |
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kagglehub==0.2.0
|
387 |
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keras-cv==0.8.2
|
388 |
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keras-nlp==0.8.2
|
389 |
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keras-tuner==1.4.6
|
390 |
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keras==3.0.5
|
391 |
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kernels-mixer==0.0.7
|
392 |
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keyring==24.3.0
|
393 |
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keyrings.google-artifactregistry-auth==1.1.2
|
394 |
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kfp-pipeline-spec==0.2.2
|
395 |
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kfp-server-api==2.0.5
|
396 |
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kfp==2.5.0
|
397 |
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kiwisolver==1.4.5
|
398 |
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kmapper==2.0.1
|
399 |
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kmodes==0.12.2
|
400 |
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korean-lunar-calendar==0.3.1
|
401 |
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kornia==0.7.2
|
402 |
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kornia_rs==0.1.2
|
403 |
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kt-legacy==1.0.5
|
404 |
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kubernetes==26.1.0
|
405 |
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langcodes==3.3.0
|
406 |
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langid==1.1.6
|
407 |
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lazy_loader==0.3
|
408 |
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learntools==0.3.4
|
409 |
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leven==1.0.4
|
410 |
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libclang==16.0.6
|
411 |
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libmambapy==1.5.0
|
412 |
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libpysal==4.9.2
|
413 |
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librosa==0.10.1
|
414 |
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lightgbm==4.2.0
|
415 |
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lightning-utilities==0.10.1
|
416 |
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lime==0.2.0.1
|
417 |
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line-profiler==4.1.2
|
418 |
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linkify-it-py==2.0.3
|
419 |
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llvmlite==0.41.1
|
420 |
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llvmlite==0.42.0
|
421 |
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lml==0.1.0
|
422 |
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locket==1.0.0
|
423 |
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loguru==0.7.2
|
424 |
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lxml==5.1.0
|
425 |
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lz4==4.3.3
|
426 |
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mamba==1.5.0
|
427 |
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mapclassify==2.6.1
|
428 |
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markdown-it-py==3.0.0
|
429 |
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markovify==0.9.4
|
430 |
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marshmallow==3.21.1
|
431 |
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matplotlib-inline==0.1.6
|
432 |
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matplotlib-venn==0.11.10
|
433 |
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matplotlib==3.7.5
|
434 |
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matplotlib==3.8.3
|
435 |
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mccabe==0.7.0
|
436 |
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mdit-py-plugins==0.4.0
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437 |
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mdurl==0.1.2
|
438 |
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memory-profiler==0.61.0
|
439 |
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menuinst==2.0.1
|
440 |
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mercantile==1.2.1
|
441 |
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mgwr==2.2.1
|
442 |
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missingno==0.5.2
|
443 |
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mistune==0.8.4
|
444 |
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mizani==0.11.0
|
445 |
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ml-dtypes==0.2.0
|
446 |
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mlcrate==0.2.0
|
447 |
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mlens==0.2.3
|
448 |
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mlxtend==0.23.1
|
449 |
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mmh3==4.1.0
|
450 |
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mne==1.6.1
|
451 |
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mnist==0.2.2
|
452 |
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mock==5.1.0
|
453 |
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momepy==0.7.0
|
454 |
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more-itertools==10.2.0
|
455 |
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mpld3==0.5.10
|
456 |
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mpmath==1.3.0
|
457 |
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msgpack-numpy==0.4.8
|
458 |
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msgpack==1.0.7
|
459 |
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multidict==6.0.4
|
460 |
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multimethod==1.10
|
461 |
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multipledispatch==1.0.0
|
462 |
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multiprocess==0.70.16
|
463 |
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munkres==1.1.4
|
464 |
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murmurhash==1.0.10
|
465 |
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mypy-extensions==1.0.0
|
466 |
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namex==0.0.7
|
467 |
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nb-conda-kernels==2.3.1
|
468 |
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nb_conda==2.2.1
|
469 |
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nbclassic==1.0.0
|
470 |
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nbclient==0.5.13
|
471 |
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nbconvert==6.4.5
|
472 |
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nbdime==3.2.0
|
473 |
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nbformat==5.9.2
|
474 |
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ndindex==1.8
|
475 |
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nest-asyncio==1.5.8
|
476 |
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networkx==3.2.1
|
477 |
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nibabel==5.2.1
|
478 |
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nilearn==0.10.3
|
479 |
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ninja==1.11.1.1
|
480 |
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nltk==3.2.4
|
481 |
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nose==1.3.7
|
482 |
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notebook==6.5.4
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483 |
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notebook==6.5.6
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484 |
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notebook_executor==0.2
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485 |
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notebook_shim==0.2.3
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486 |
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numba==0.58.1
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487 |
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numba==0.59.0
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488 |
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numexpr==2.9.0
|
489 |
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numpy==1.26.4
|
490 |
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nvidia-ml-py==11.495.46
|
491 |
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nvtx==0.2.10
|
492 |
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oauth2client==4.1.3
|
493 |
+
oauthlib==3.2.2
|
494 |
+
objsize==0.6.1
|
495 |
+
odfpy==1.4.1
|
496 |
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olefile==0.47
|
497 |
+
onnx==1.15.0
|
498 |
+
opencensus-context==0.1.3
|
499 |
+
opencensus==0.11.4
|
500 |
+
opencv-contrib-python==4.9.0.80
|
501 |
+
opencv-python-headless==4.9.0.80
|
502 |
+
opencv-python==4.9.0.80
|
503 |
+
openpyxl==3.1.2
|
504 |
+
openslide-python==1.3.1
|
505 |
+
opentelemetry-api==1.22.0
|
506 |
+
opentelemetry-exporter-otlp-proto-common==1.22.0
|
507 |
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opentelemetry-exporter-otlp-proto-grpc==1.22.0
|
508 |
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opentelemetry-exporter-otlp-proto-http==1.22.0
|
509 |
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opentelemetry-exporter-otlp==1.22.0
|
510 |
+
opentelemetry-proto==1.22.0
|
511 |
+
opentelemetry-sdk==1.22.0
|
512 |
+
opentelemetry-semantic-conventions==0.43b0
|
513 |
+
opt-einsum==3.3.0
|
514 |
+
optax==0.2.1
|
515 |
+
optimum==1.18.0
|
516 |
+
optuna==3.6.0
|
517 |
+
orbax-checkpoint==0.5.6
|
518 |
+
ordered-set==4.1.0
|
519 |
+
orjson==3.9.10
|
520 |
+
ortools==9.4.1874
|
521 |
+
osmnx==1.9.1
|
522 |
+
overrides==7.4.0
|
523 |
+
packaging==21.3
|
524 |
+
pandas-datareader==0.10.0
|
525 |
+
pandas-profiling==3.6.6
|
526 |
+
pandas-summary==0.2.0
|
527 |
+
pandas==2.1.4
|
528 |
+
pandas==2.2.1
|
529 |
+
pandasql==0.7.3
|
530 |
+
pandocfilters==1.5.0
|
531 |
+
panel==1.3.8
|
532 |
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papermill==2.5.0
|
533 |
+
param==2.0.2
|
534 |
+
parso==0.8.3
|
535 |
+
partd==1.4.1
|
536 |
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path.py==12.5.0
|
537 |
+
path==16.10.0
|
538 |
+
pathos==0.3.2
|
539 |
+
pathy==0.10.3
|
540 |
+
patsy==0.5.6
|
541 |
+
pdf2image==1.17.0
|
542 |
+
peft==0.10.0
|
543 |
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pettingzoo==1.24.0
|
544 |
+
pexpect==4.8.0
|
545 |
+
pexpect==4.9.0
|
546 |
+
phik==0.12.4
|
547 |
+
pickleshare==0.7.5
|
548 |
+
pip==23.3.2
|
549 |
+
pkgutil_resolve_name==1.3.10
|
550 |
+
platformdirs==4.2.0
|
551 |
+
plotly-express==0.4.1
|
552 |
+
plotly==5.18.0
|
553 |
+
plotnine==0.13.2
|
554 |
+
pluggy==1.4.0
|
555 |
+
pointpats==2.4.0
|
556 |
+
polars==0.20.15
|
557 |
+
polyglot==16.7.4
|
558 |
+
pooch==1.8.1
|
559 |
+
pox==0.3.4
|
560 |
+
ppca==0.0.4
|
561 |
+
ppft==1.7.6.8
|
562 |
+
preprocessing==0.1.13
|
563 |
+
preshed==3.0.9
|
564 |
+
prettytable==3.9.0
|
565 |
+
progressbar2==4.4.2
|
566 |
+
prometheus-client==0.19.0
|
567 |
+
promise==2.3
|
568 |
+
prompt-toolkit==3.0.42
|
569 |
+
prompt-toolkit==3.0.43
|
570 |
+
pronouncing==0.2.0
|
571 |
+
prophet==1.1.1
|
572 |
+
proto-plus==1.23.0
|
573 |
+
protobuf==3.20.3
|
574 |
+
protobuf==4.21.12
|
575 |
+
psutil==5.9.3
|
576 |
+
psutil==5.9.7
|
577 |
+
ptyprocess==0.7.0
|
578 |
+
pudb==2024.1
|
579 |
+
pure-eval==0.2.2
|
580 |
+
py-cpuinfo==9.0.0
|
581 |
+
py-spy==0.3.14
|
582 |
+
py4j==0.10.9.7
|
583 |
+
pyLDAvis==3.4.1
|
584 |
+
pyOpenSSL==23.3.0
|
585 |
+
pyaml==23.12.0
|
586 |
+
pyarrow==11.0.0
|
587 |
+
pyasn1-modules==0.3.0
|
588 |
+
pyasn1==0.5.1
|
589 |
+
pybind11==2.11.1
|
590 |
+
pyclipper==1.3.0.post5
|
591 |
+
pycodestyle==2.11.1
|
592 |
+
pycosat==0.6.6
|
593 |
+
pycparser==2.21
|
594 |
+
pycryptodome==3.20.0
|
595 |
+
pyct==0.5.0
|
596 |
+
pycuda==2024.1
|
597 |
+
pydantic==2.5.3
|
598 |
+
pydantic==2.6.4
|
599 |
+
pydantic_core==2.14.6
|
600 |
+
pydantic_core==2.16.3
|
601 |
+
pydegensac==0.1.2
|
602 |
+
pydicom==2.4.4
|
603 |
+
pydocstyle==6.3.0
|
604 |
+
pydot==1.4.2
|
605 |
+
pydub==0.25.1
|
606 |
+
pyemd==1.0.0
|
607 |
+
pyerfa==2.0.1.1
|
608 |
+
pyexcel-io==0.6.6
|
609 |
+
pyexcel-ods==0.6.0
|
610 |
+
pyflakes==3.2.0
|
611 |
+
pygltflib==1.16.2
|
612 |
+
pykalman==0.9.5
|
613 |
+
pylibraft==23.8.0
|
614 |
+
pylint==3.0.4
|
615 |
+
pymc3==3.11.4
|
616 |
+
pymongo==3.13.0
|
617 |
+
pynndescent==0.5.11
|
618 |
+
pynvml==11.4.1
|
619 |
+
pynvrtc==9.2
|
620 |
+
pyocr==0.8.5
|
621 |
+
pyparsing==3.1.1
|
622 |
+
pyparsing==3.1.2
|
623 |
+
pypdf==4.1.0
|
624 |
+
pyproj==3.6.1
|
625 |
+
pysal==24.1
|
626 |
+
pyshp==2.3.1
|
627 |
+
pytesseract==0.3.10
|
628 |
+
pytest==8.1.1
|
629 |
+
python-Levenshtein==0.25.0
|
630 |
+
python-bidi==0.4.2
|
631 |
+
python-dateutil==2.9.0.post0
|
632 |
+
python-dotenv==1.0.0
|
633 |
+
python-json-logger==2.0.7
|
634 |
+
python-louvain==0.16
|
635 |
+
python-lsp-jsonrpc==1.1.2
|
636 |
+
python-lsp-server==1.10.1
|
637 |
+
python-slugify==8.0.4
|
638 |
+
python-utils==3.8.2
|
639 |
+
pythreejs==2.4.2
|
640 |
+
pytoolconfig==1.3.1
|
641 |
+
pytools==2023.1.1
|
642 |
+
pytorch-ignite==0.4.13
|
643 |
+
pytorch-lightning==2.2.1
|
644 |
+
pytz==2023.3.post1
|
645 |
+
pytz==2024.1
|
646 |
+
pyu2f==0.1.5
|
647 |
+
pyviz_comms==3.0.1
|
648 |
+
pyzmq==24.0.1
|
649 |
+
pyzmq==25.1.2
|
650 |
+
qgrid==1.3.1
|
651 |
+
qtconsole==5.5.1
|
652 |
+
quantecon==0.7.2
|
653 |
+
quantities==0.15.0
|
654 |
+
qudida==0.0.4
|
655 |
+
raft-dask==23.8.0
|
656 |
+
rapidfuzz==3.6.2
|
657 |
+
rasterio==1.3.9
|
658 |
+
rasterstats==0.19.0
|
659 |
+
ray-cpp==2.9.0
|
660 |
+
ray==2.9.0
|
661 |
+
referencing==0.32.1
|
662 |
+
regex==2023.12.25
|
663 |
+
requests-oauthlib==1.3.1
|
664 |
+
requests-toolbelt==0.10.1
|
665 |
+
requests==2.31.0
|
666 |
+
responses==0.18.0
|
667 |
+
retrying==1.3.3
|
668 |
+
retrying==1.3.4
|
669 |
+
rfc3339-validator==0.1.4
|
670 |
+
rfc3986-validator==0.1.1
|
671 |
+
rgf-python==3.12.0
|
672 |
+
rich-click==1.7.4
|
673 |
+
rich==13.7.0
|
674 |
+
rich==13.7.1
|
675 |
+
rmm==23.8.0
|
676 |
+
rope==1.12.0
|
677 |
+
rouge==1.0.1
|
678 |
+
rpds-py==0.16.2
|
679 |
+
rsa==4.9
|
680 |
+
ruamel-yaml-conda==0.15.100
|
681 |
+
ruamel.yaml.clib==0.2.7
|
682 |
+
ruamel.yaml==0.17.40
|
683 |
+
s2sphere==0.2.5
|
684 |
+
s3fs==2024.3.0
|
685 |
+
s3transfer==0.6.2
|
686 |
+
safetensors==0.4.2
|
687 |
+
scattertext==0.1.19
|
688 |
+
scikit-image==0.22.0
|
689 |
+
scikit-learn-intelex==2024.1.0
|
690 |
+
scikit-learn==1.2.2
|
691 |
+
scikit-multilearn==0.2.0
|
692 |
+
scikit-optimize==0.10.1
|
693 |
+
scikit-plot==0.3.7
|
694 |
+
scikit-surprise==1.1.3
|
695 |
+
scipy==1.11.4
|
696 |
+
scipy==1.12.0
|
697 |
+
seaborn==0.12.2
|
698 |
+
segment_anything==1.0
|
699 |
+
segregation==2.5
|
700 |
+
semver==3.0.2
|
701 |
+
sentencepiece==0.2.0
|
702 |
+
sentry-sdk==1.42.0
|
703 |
+
setproctitle==1.3.3
|
704 |
+
setuptools-git==1.2
|
705 |
+
setuptools-scm==8.0.4
|
706 |
+
setuptools==69.0.3
|
707 |
+
shap==0.44.1
|
708 |
+
shapely==2.0.3
|
709 |
+
shellingham==1.5.4
|
710 |
+
simpervisor==1.0.0
|
711 |
+
simplejson==3.19.2
|
712 |
+
six==1.16.0
|
713 |
+
sklearn-pandas==2.2.0
|
714 |
+
slicer==0.0.7
|
715 |
+
smart-open==6.4.0
|
716 |
+
smmap==5.0.1
|
717 |
+
sniffio==1.3.0
|
718 |
+
snowballstemmer==2.2.0
|
719 |
+
snuggs==1.4.7
|
720 |
+
sortedcontainers==2.4.0
|
721 |
+
soundfile==0.12.1
|
722 |
+
soupsieve==2.5
|
723 |
+
soxr==0.3.7
|
724 |
+
spacy-legacy==3.0.12
|
725 |
+
spacy-loggers==1.0.5
|
726 |
+
spacy==3.7.2
|
727 |
+
spaghetti==1.7.5.post1
|
728 |
+
spectral==0.23.1
|
729 |
+
spglm==1.1.0
|
730 |
+
sphinx-rtd-theme==0.2.4
|
731 |
+
spint==1.0.7
|
732 |
+
splot==1.1.5.post1
|
733 |
+
spopt==0.6.0
|
734 |
+
spreg==1.4.2
|
735 |
+
spvcm==0.3.0
|
736 |
+
sqlparse==0.4.4
|
737 |
+
squarify==0.4.3
|
738 |
+
srsly==2.4.8
|
739 |
+
stable-baselines3==2.1.0
|
740 |
+
stack-data==0.6.2
|
741 |
+
stack-data==0.6.3
|
742 |
+
stanio==0.3.0
|
743 |
+
starlette==0.32.0.post1
|
744 |
+
statsmodels==0.14.1
|
745 |
+
stemming==1.0.1
|
746 |
+
stop-words==2018.7.23
|
747 |
+
stopit==1.1.2
|
748 |
+
stumpy==1.12.0
|
749 |
+
sympy==1.12
|
750 |
+
tables==3.9.2
|
751 |
+
tabulate==0.9.0
|
752 |
+
tangled-up-in-unicode==0.2.0
|
753 |
+
tbb==2021.11.0
|
754 |
+
tblib==3.0.0
|
755 |
+
tenacity==8.2.3
|
756 |
+
tensorboard-data-server==0.7.2
|
757 |
+
tensorboard-plugin-profile==2.15.0
|
758 |
+
tensorboard==2.15.1
|
759 |
+
tensorboardX==2.6.2.2
|
760 |
+
tensorflow-cloud==0.1.16
|
761 |
+
tensorflow-datasets==4.9.4
|
762 |
+
tensorflow-decision-forests==1.8.1
|
763 |
+
tensorflow-estimator==2.15.0
|
764 |
+
tensorflow-hub==0.16.1
|
765 |
+
tensorflow-io-gcs-filesystem==0.35.0
|
766 |
+
tensorflow-io==0.35.0
|
767 |
+
tensorflow-metadata==0.14.0
|
768 |
+
tensorflow-probability==0.23.0
|
769 |
+
tensorflow-serving-api==2.14.1
|
770 |
+
tensorflow-text==2.15.0
|
771 |
+
tensorflow-transform==0.14.0
|
772 |
+
tensorflow==2.15.0
|
773 |
+
tensorpack==0.11
|
774 |
+
tensorstore==0.1.56
|
775 |
+
termcolor==2.4.0
|
776 |
+
terminado==0.18.0
|
777 |
+
testpath==0.6.0
|
778 |
+
text-unidecode==1.3
|
779 |
+
textblob==0.18.0.post0
|
780 |
+
texttable==1.7.0
|
781 |
+
tf_keras==2.15.1
|
782 |
+
tfp-nightly==0.24.0.dev0
|
783 |
+
thinc==8.2.2
|
784 |
+
threadpoolctl==3.2.0
|
785 |
+
tifffile==2023.12.9
|
786 |
+
timm==0.9.16
|
787 |
+
tinycss2==1.2.1
|
788 |
+
tobler==0.11.2
|
789 |
+
tokenizers==0.15.2
|
790 |
+
toml==0.10.2
|
791 |
+
tomli==2.0.1
|
792 |
+
tomlkit==0.12.4
|
793 |
+
toolz==0.12.1
|
794 |
+
torch==2.1.2
|
795 |
+
torchaudio==2.1.2
|
796 |
+
torchdata==0.7.1
|
797 |
+
torchinfo==1.8.0
|
798 |
+
torchmetrics==1.3.2
|
799 |
+
torchtext==0.16.2
|
800 |
+
torchvision==0.16.2
|
801 |
+
tornado==6.3.3
|
802 |
+
tqdm==4.66.1
|
803 |
+
traceml==1.0.8
|
804 |
+
traitlets==5.9.0
|
805 |
+
traittypes==0.2.1
|
806 |
+
transformers==4.38.2
|
807 |
+
treelite-runtime==3.2.0
|
808 |
+
treelite==3.2.0
|
809 |
+
trueskill==0.4.5
|
810 |
+
truststore==0.8.0
|
811 |
+
trx-python==0.2.9
|
812 |
+
tsfresh==0.20.2
|
813 |
+
typeguard==4.1.5
|
814 |
+
typer==0.9.0
|
815 |
+
types-python-dateutil==2.8.19.20240106
|
816 |
+
typing-inspect==0.9.0
|
817 |
+
typing-utils==0.1.0
|
818 |
+
typing_extensions==4.9.0
|
819 |
+
tzdata==2023.4
|
820 |
+
uc-micro-py==1.0.3
|
821 |
+
ucx-py==0.33.0
|
822 |
+
ujson==5.9.0
|
823 |
+
umap-learn==0.5.5
|
824 |
+
unicodedata2==15.1.0
|
825 |
+
update-checker==0.18.0
|
826 |
+
uri-template==1.3.0
|
827 |
+
uritemplate==3.0.1
|
828 |
+
urllib3==1.26.18
|
829 |
+
urllib3==2.1.0
|
830 |
+
urwid==2.6.9
|
831 |
+
urwid_readline==0.14
|
832 |
+
uvicorn==0.25.0
|
833 |
+
uvloop==0.19.0
|
834 |
+
vaex-astro==0.9.3
|
835 |
+
vaex-core==4.17.1
|
836 |
+
vaex-hdf5==0.14.1
|
837 |
+
vaex-jupyter==0.8.2
|
838 |
+
vaex-ml==0.18.3
|
839 |
+
vaex-server==0.9.0
|
840 |
+
vaex-viz==0.5.4
|
841 |
+
vaex==4.17.0
|
842 |
+
vec_noise==1.1.4
|
843 |
+
vecstack==0.4.0
|
844 |
+
virtualenv==20.21.0
|
845 |
+
visions==0.7.5
|
846 |
+
vowpalwabbit==9.9.0
|
847 |
+
vtk==9.3.0
|
848 |
+
wandb==0.16.4
|
849 |
+
wasabi==1.1.2
|
850 |
+
watchfiles==0.21.0
|
851 |
+
wavio==0.0.8
|
852 |
+
wcwidth==0.2.13
|
853 |
+
weasel==0.3.4
|
854 |
+
webcolors==1.13
|
855 |
+
webencodings==0.5.1
|
856 |
+
websocket-client==1.7.0
|
857 |
+
websockets==12.0
|
858 |
+
wfdb==4.1.2
|
859 |
+
whatthepatch==1.0.5
|
860 |
+
wheel==0.42.0
|
861 |
+
widgetsnbextension==3.6.6
|
862 |
+
witwidget==1.8.1
|
863 |
+
woodwork==0.29.0
|
864 |
+
wordcloud==1.9.3
|
865 |
+
wordsegment==1.3.1
|
866 |
+
wrapt==1.14.1
|
867 |
+
xarray-einstats==0.7.0
|
868 |
+
xarray==2024.2.0
|
869 |
+
xgboost==2.0.3
|
870 |
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wandb/run-20240401_093743-ie4jv7u5/files/wandb-metadata.json
ADDED
@@ -0,0 +1,66 @@
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1 |
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wandb/run-20240401_093743-ie4jv7u5/files/wandb-summary.json
ADDED
@@ -0,0 +1 @@
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{"train/loss": 0.788, "train/grad_norm": 0.9128203988075256, "train/learning_rate": 0.00013877551020408165, "train/epoch": 12.0, "train/global_step": 16, "_timestamp": 1711964681.5606613, "_runtime": 418.4748373031616, "_step": 31, "eval/loss": 1.0970141887664795, "eval/runtime": 1.8296, "eval/samples_per_second": 1.093, "eval/steps_per_second": 0.547}
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wandb/run-20240401_093743-ie4jv7u5/logs/debug-internal.log
ADDED
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1 |
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2024-04-01 09:37:43,083 INFO StreamThr :119 [internal.py:wandb_internal():86] W&B internal server running at pid: 119, started at: 2024-04-01 09:37:43.082780
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2024-04-01 09:37:43,596 INFO WriterThread:119 [datastore.py:open_for_write():87] open: /kaggle/working/wandb/run-20240401_093743-ie4jv7u5/run-ie4jv7u5.wandb
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4 |
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2024-04-01 09:37:43,597 DEBUG SenderThread:119 [sender.py:send():378] send: header
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2024-04-01 09:37:43,600 DEBUG SenderThread:119 [sender.py:send():378] send: run
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2024-04-01 09:37:43,758 INFO SenderThread:119 [dir_watcher.py:__init__():211] watching files in: /kaggle/working/wandb/run-20240401_093743-ie4jv7u5/files
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2024-04-01 09:37:43,758 INFO SenderThread:119 [sender.py:_start_run_threads():1099] run started: ie4jv7u5 with start time 1711964263.085824
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2024-04-01 09:37:43,766 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: check_version
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2024-04-01 09:37:43,766 DEBUG SenderThread:119 [sender.py:send_request():405] send_request: check_version
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2024-04-01 09:37:43,860 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: run_start
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2024-04-01 09:37:43,872 DEBUG HandlerThread:119 [system_info.py:__init__():26] System info init
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2024-04-01 09:37:43,872 DEBUG HandlerThread:119 [system_info.py:__init__():41] System info init done
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2024-04-01 09:37:43,872 INFO HandlerThread:119 [system_monitor.py:start():194] Starting system monitor
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2024-04-01 09:37:43,872 INFO SystemMonitor:119 [system_monitor.py:_start():158] Starting system asset monitoring threads
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2024-04-01 09:37:43,872 INFO HandlerThread:119 [system_monitor.py:probe():214] Collecting system info
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2024-04-01 09:37:43,873 INFO SystemMonitor:119 [interfaces.py:start():190] Started cpu monitoring
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2024-04-01 09:37:43,873 INFO SystemMonitor:119 [interfaces.py:start():190] Started disk monitoring
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2024-04-01 09:37:43,875 INFO SystemMonitor:119 [interfaces.py:start():190] Started gpu monitoring
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2024-04-01 09:37:43,876 INFO SystemMonitor:119 [interfaces.py:start():190] Started memory monitoring
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2024-04-01 09:37:43,877 INFO SystemMonitor:119 [interfaces.py:start():190] Started network monitoring
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2024-04-01 09:37:43,894 DEBUG HandlerThread:119 [system_info.py:probe():150] Probing system
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2024-04-01 09:37:43,896 DEBUG HandlerThread:119 [gitlib.py:_init_repo():56] git repository is invalid
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2024-04-01 09:37:43,896 DEBUG HandlerThread:119 [system_info.py:probe():198] Probing system done
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2024-04-01 09:37:43,896 DEBUG HandlerThread:119 [system_monitor.py:probe():223] {'os': 'Linux-5.15.133+-x86_64-with-glibc2.31', 'python': '3.10.13', 'heartbeatAt': '2024-04-01T09:37:43.894456', 'startedAt': '2024-04-01T09:37:43.076491', 'docker': None, 'cuda': None, 'args': (), 'state': 'running', 'program': 'kaggle.ipynb', 'codePathLocal': None, 'root': '/kaggle/working', 'host': '148e249fd8ed', 'username': 'root', 'executable': '/opt/conda/bin/python3.10', 'cpu_count': 2, 'cpu_count_logical': 4, 'cpu_freq': {'current': 2000.142, 'min': 0.0, 'max': 0.0}, 'cpu_freq_per_core': [{'current': 2000.142, 'min': 0.0, 'max': 0.0}, {'current': 2000.142, 'min': 0.0, 'max': 0.0}, {'current': 2000.142, 'min': 0.0, 'max': 0.0}, {'current': 2000.142, 'min': 0.0, 'max': 0.0}], 'disk': {'/': {'total': 8062.387607574463, 'used': 5524.099212646484}}, 'gpu': 'Tesla T4', 'gpu_count': 2, 'gpu_devices': [{'name': 'Tesla T4', 'memory_total': 16106127360}, {'name': 'Tesla T4', 'memory_total': 16106127360}], 'memory': {'total': 31.357559204101562}}
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25 |
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2024-04-01 09:37:43,896 INFO HandlerThread:119 [system_monitor.py:probe():224] Finished collecting system info
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26 |
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2024-04-01 09:37:43,896 INFO HandlerThread:119 [system_monitor.py:probe():227] Publishing system info
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2024-04-01 09:37:43,896 DEBUG HandlerThread:119 [system_info.py:_save_conda():207] Saving list of conda packages installed into the current environment
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2024-04-01 09:37:44,760 INFO Thread-12 :119 [dir_watcher.py:_on_file_created():271] file/dir created: /kaggle/working/wandb/run-20240401_093743-ie4jv7u5/files/conda-environment.yaml
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2024-04-01 09:38:42,776 INFO Thread-12 :119 [dir_watcher.py:_on_file_modified():288] file/dir modified: /kaggle/working/wandb/run-20240401_093743-ie4jv7u5/files/conda-environment.yaml
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2024-04-01 09:38:42,892 DEBUG SenderThread:119 [sender.py:send():378] send: history
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2024-04-01 09:38:42,896 INFO SenderThread:119 [sender.py:_save_file():1365] saving file wandb-summary.json with policy end
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2024-04-01 09:38:42,897 INFO SenderThread:119 [sender.py:_save_file():1365] saving file wandb-summary.json with policy end
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2024-04-01 09:38:42,898 INFO SenderThread:119 [sender.py:_save_file():1365] saving file wandb-summary.json with policy end
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2024-04-01 09:38:42,899 INFO SenderThread:119 [sender.py:_save_file():1365] saving file wandb-metadata.json with policy now
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2024-04-01 09:38:43,776 INFO Thread-12 :119 [dir_watcher.py:_on_file_created():271] file/dir created: /kaggle/working/wandb/run-20240401_093743-ie4jv7u5/files/wandb-summary.json
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2024-04-01 09:38:43,777 INFO Thread-12 :119 [dir_watcher.py:_on_file_created():271] file/dir created: /kaggle/working/wandb/run-20240401_093743-ie4jv7u5/files/wandb-metadata.json
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2024-04-01 09:38:43,777 INFO Thread-12 :119 [dir_watcher.py:_on_file_created():271] file/dir created: /kaggle/working/wandb/run-20240401_093743-ie4jv7u5/files/requirements.txt
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2024-04-01 09:38:43,777 INFO Thread-12 :119 [dir_watcher.py:_on_file_created():271] file/dir created: /kaggle/working/wandb/run-20240401_093743-ie4jv7u5/files/output.log
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2024-04-01 09:38:43,877 DEBUG SystemMonitor:119 [system_monitor.py:_start():172] Starting system metrics aggregation loop
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2024-04-01 09:38:44,777 INFO Thread-12 :119 [dir_watcher.py:_on_file_modified():288] file/dir modified: /kaggle/working/wandb/run-20240401_093743-ie4jv7u5/files/config.yaml
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2024-04-01 09:38:44,908 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
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2024-04-01 09:38:45,777 INFO Thread-12 :119 [dir_watcher.py:_on_file_modified():288] file/dir modified: /kaggle/working/wandb/run-20240401_093743-ie4jv7u5/files/output.log
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2024-04-01 09:38:49,013 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: status_report
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2024-04-01 09:38:55,054 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: pause
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2024-04-01 09:38:55,055 INFO HandlerThread:119 [handler.py:handle_request_pause():708] stopping system metrics thread
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2024-04-01 09:38:55,056 INFO HandlerThread:119 [interfaces.py:finish():202] Joined cpu monitor
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2024-04-01 09:38:55,056 INFO HandlerThread:119 [interfaces.py:finish():202] Joined disk monitor
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2024-04-01 09:38:55,067 INFO HandlerThread:119 [interfaces.py:finish():202] Joined memory monitor
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2024-04-01 09:38:55,067 INFO HandlerThread:119 [interfaces.py:finish():202] Joined network monitor
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2024-04-01 09:38:55,067 DEBUG SenderThread:119 [sender.py:send():378] send: stats
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2024-04-01 09:38:59,068 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: status_report
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2024-04-01 09:38:59,927 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
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2024-04-01 09:39:21,056 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: resume
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2024-04-01 09:39:21,056 INFO HandlerThread:119 [handler.py:handle_request_resume():699] starting system metrics thread
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2024-04-01 09:39:21,057 INFO SystemMonitor:119 [interfaces.py:start():190] Started disk monitoring
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2024-04-01 09:39:21,059 INFO SystemMonitor:119 [interfaces.py:start():190] Started memory monitoring
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2024-04-01 09:39:21,061 INFO SystemMonitor:119 [interfaces.py:start():190] Started network monitoring
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2024-04-01 09:39:21,062 INFO HandlerThread:119 [interfaces.py:finish():202] Joined cpu monitor
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2024-04-01 09:39:21,063 DEBUG SystemMonitor:119 [system_monitor.py:_start():172] Starting system metrics aggregation loop
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2024-04-01 09:39:21,063 DEBUG SystemMonitor:119 [system_monitor.py:_start():179] Finished system metrics aggregation loop
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2024-04-01 09:39:21,063 DEBUG SystemMonitor:119 [system_monitor.py:_start():183] Publishing last batch of metrics
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2024-04-01 09:39:21,082 INFO HandlerThread:119 [interfaces.py:finish():202] Joined network monitor
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2024-04-01 09:39:21,083 DEBUG SenderThread:119 [sender.py:send():378] send: stats
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2024-04-01 09:39:21,460 INFO SystemMonitor:119 [interfaces.py:start():190] Started disk monitoring
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2024-04-01 09:39:21,462 INFO SystemMonitor:119 [interfaces.py:start():190] Started gpu monitoring
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2024-04-01 09:39:21,463 INFO SystemMonitor:119 [interfaces.py:start():190] Started memory monitoring
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2024-04-01 09:39:21,463 INFO SystemMonitor:119 [interfaces.py:start():190] Started network monitoring
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2024-04-01 09:39:22,013 DEBUG SenderThread:119 [sender.py:send():378] send: config
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2024-04-01 09:39:22,014 DEBUG SenderThread:119 [sender.py:send():378] send: metric
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2024-04-01 09:39:22,014 WARNING SenderThread:119 [sender.py:send_metric():1316] Seen metric with glob (shouldn't happen)
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2024-04-01 09:39:24,966 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
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2024-04-01 09:39:33,470 DEBUG SenderThread:119 [sender.py:send_request():405] send_request: summary_record
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2024-04-01 09:39:33,471 INFO SenderThread:119 [sender.py:_save_file():1365] saving file wandb-summary.json with policy end
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2024-04-01 09:39:33,797 INFO Thread-12 :119 [dir_watcher.py:_on_file_modified():288] file/dir modified: /kaggle/working/wandb/run-20240401_093743-ie4jv7u5/files/wandb-summary.json
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2024-04-01 09:39:34,968 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
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2024-04-01 09:39:35,168 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: partial_history
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2024-04-01 09:39:35,169 DEBUG SenderThread:119 [sender.py:send():378] send: history
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2024-04-01 09:39:35,169 DEBUG SenderThread:119 [sender.py:send_request():405] send_request: summary_record
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2024-04-01 09:39:35,169 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: status_report
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2024-04-01 09:39:35,170 INFO SenderThread:119 [sender.py:_save_file():1365] saving file wandb-summary.json with policy end
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2024-04-01 09:39:35,798 INFO Thread-12 :119 [dir_watcher.py:_on_file_modified():288] file/dir modified: /kaggle/working/wandb/run-20240401_093743-ie4jv7u5/files/wandb-summary.json
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2024-04-01 09:39:37,798 INFO Thread-12 :119 [dir_watcher.py:_on_file_modified():288] file/dir modified: /kaggle/working/wandb/run-20240401_093743-ie4jv7u5/files/output.log
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2024-04-01 09:39:39,970 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
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2024-04-01 09:39:45,801 INFO Thread-12 :119 [dir_watcher.py:_on_file_modified():288] file/dir modified: /kaggle/working/wandb/run-20240401_093743-ie4jv7u5/files/config.yaml
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2024-04-01 09:39:46,821 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: partial_history
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2024-04-01 09:39:46,823 DEBUG SenderThread:119 [sender.py:send():378] send: history
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2024-04-01 09:39:46,825 INFO SenderThread:119 [sender.py:_save_file():1365] saving file wandb-summary.json with policy end
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2024-04-01 09:39:47,802 INFO Thread-12 :119 [dir_watcher.py:_on_file_modified():288] file/dir modified: /kaggle/working/wandb/run-20240401_093743-ie4jv7u5/files/wandb-summary.json
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2024-04-01 09:39:48,560 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: partial_history
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2024-04-01 09:39:48,562 DEBUG SenderThread:119 [sender.py:send():378] send: history
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2024-04-01 09:39:48,562 DEBUG SenderThread:119 [sender.py:send_request():405] send_request: summary_record
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2024-04-01 09:39:48,562 INFO SenderThread:119 [sender.py:_save_file():1365] saving file wandb-summary.json with policy end
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2024-04-01 09:39:48,803 INFO Thread-12 :119 [dir_watcher.py:_on_file_modified():288] file/dir modified: /kaggle/working/wandb/run-20240401_093743-ie4jv7u5/files/wandb-summary.json
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2024-04-01 09:39:49,972 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
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2024-04-01 09:39:50,748 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: status_report
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2024-04-01 09:39:51,804 INFO Thread-12 :119 [dir_watcher.py:_on_file_modified():288] file/dir modified: /kaggle/working/wandb/run-20240401_093743-ie4jv7u5/files/output.log
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2024-04-01 09:39:54,973 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
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2024-04-01 09:39:55,749 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: status_report
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2024-04-01 09:39:59,406 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: pause
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2024-04-01 09:39:59,406 INFO HandlerThread:119 [handler.py:handle_request_pause():708] stopping system metrics thread
|
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2024-04-01 09:39:59,406 INFO HandlerThread:119 [system_monitor.py:finish():203] Stopping system monitor
|
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2024-04-01 09:39:59,406 DEBUG SystemMonitor:119 [system_monitor.py:_start():172] Starting system metrics aggregation loop
|
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2024-04-01 09:39:59,407 DEBUG SystemMonitor:119 [system_monitor.py:_start():179] Finished system metrics aggregation loop
|
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2024-04-01 09:39:59,407 DEBUG SystemMonitor:119 [system_monitor.py:_start():183] Publishing last batch of metrics
|
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2024-04-01 09:39:59,407 INFO HandlerThread:119 [interfaces.py:finish():202] Joined cpu monitor
|
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2024-04-01 09:39:59,409 INFO HandlerThread:119 [interfaces.py:finish():202] Joined disk monitor
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2024-04-01 09:39:59,420 DEBUG SenderThread:119 [sender.py:send():378] send: stats
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2024-04-01 09:39:59,974 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
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2024-04-01 09:40:01,420 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: status_report
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2024-04-01 09:40:04,975 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
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2024-04-01 09:40:19,979 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
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2024-04-01 09:40:21,424 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: status_report
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2024-04-01 09:40:24,979 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
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2024-04-01 09:40:26,425 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: status_report
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2024-04-01 09:40:29,980 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
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2024-04-01 09:40:31,426 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: status_report
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2024-04-01 09:40:34,981 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
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2024-04-01 09:40:36,426 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: status_report
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2024-04-01 09:40:39,982 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
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2024-04-01 09:40:41,427 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: status_report
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2024-04-01 09:40:44,983 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
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2024-04-01 09:40:46,428 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: status_report
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2024-04-01 09:40:49,984 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
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2024-04-01 09:40:51,429 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: status_report
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2024-04-01 09:40:54,985 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
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2024-04-01 09:40:56,430 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: status_report
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2024-04-01 09:40:59,986 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
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2024-04-01 09:41:00,164 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: resume
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2024-04-01 09:41:00,164 INFO HandlerThread:119 [handler.py:handle_request_resume():699] starting system metrics thread
|
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2024-04-01 09:41:00,164 INFO HandlerThread:119 [system_monitor.py:start():194] Starting system monitor
|
239 |
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2024-04-01 09:41:00,164 INFO SystemMonitor:119 [system_monitor.py:_start():158] Starting system asset monitoring threads
|
240 |
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2024-04-01 09:41:00,165 INFO SystemMonitor:119 [interfaces.py:start():190] Started cpu monitoring
|
241 |
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2024-04-01 09:41:00,165 INFO SystemMonitor:119 [interfaces.py:start():190] Started disk monitoring
|
242 |
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2024-04-01 09:41:00,166 INFO SystemMonitor:119 [interfaces.py:start():190] Started gpu monitoring
|
243 |
+
2024-04-01 09:41:00,166 INFO SystemMonitor:119 [interfaces.py:start():190] Started memory monitoring
|
244 |
+
2024-04-01 09:41:00,168 INFO SystemMonitor:119 [interfaces.py:start():190] Started network monitoring
|
245 |
+
2024-04-01 09:41:00,170 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: pause
|
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2024-04-01 09:41:00,170 INFO HandlerThread:119 [handler.py:handle_request_pause():708] stopping system metrics thread
|
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2024-04-01 09:41:00,170 INFO HandlerThread:119 [system_monitor.py:finish():203] Stopping system monitor
|
248 |
+
2024-04-01 09:41:00,171 DEBUG SystemMonitor:119 [system_monitor.py:_start():172] Starting system metrics aggregation loop
|
249 |
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2024-04-01 09:41:00,171 INFO HandlerThread:119 [interfaces.py:finish():202] Joined cpu monitor
|
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2024-04-01 09:41:00,171 DEBUG SystemMonitor:119 [system_monitor.py:_start():179] Finished system metrics aggregation loop
|
251 |
+
2024-04-01 09:41:00,172 DEBUG SystemMonitor:119 [system_monitor.py:_start():183] Publishing last batch of metrics
|
252 |
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2024-04-01 09:41:00,174 INFO HandlerThread:119 [interfaces.py:finish():202] Joined disk monitor
|
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+
2024-04-01 09:41:00,192 INFO HandlerThread:119 [interfaces.py:finish():202] Joined gpu monitor
|
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+
2024-04-01 09:41:00,192 INFO HandlerThread:119 [interfaces.py:finish():202] Joined memory monitor
|
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+
2024-04-01 09:41:00,192 INFO HandlerThread:119 [interfaces.py:finish():202] Joined network monitor
|
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+
2024-04-01 09:41:00,193 DEBUG SenderThread:119 [sender.py:send():378] send: stats
|
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2024-04-01 09:41:02,194 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: status_report
|
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2024-04-01 09:41:04,987 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
|
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2024-04-01 09:41:07,195 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: status_report
|
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2024-04-01 09:41:07,655 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: resume
|
261 |
+
2024-04-01 09:41:07,655 INFO HandlerThread:119 [handler.py:handle_request_resume():699] starting system metrics thread
|
262 |
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2024-04-01 09:41:07,655 INFO HandlerThread:119 [system_monitor.py:start():194] Starting system monitor
|
263 |
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2024-04-01 09:41:07,655 INFO SystemMonitor:119 [system_monitor.py:_start():158] Starting system asset monitoring threads
|
264 |
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2024-04-01 09:41:07,656 INFO SystemMonitor:119 [interfaces.py:start():190] Started cpu monitoring
|
265 |
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2024-04-01 09:41:07,656 INFO SystemMonitor:119 [interfaces.py:start():190] Started disk monitoring
|
266 |
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2024-04-01 09:41:07,657 INFO SystemMonitor:119 [interfaces.py:start():190] Started gpu monitoring
|
267 |
+
2024-04-01 09:41:07,658 INFO SystemMonitor:119 [interfaces.py:start():190] Started memory monitoring
|
268 |
+
2024-04-01 09:41:07,658 INFO SystemMonitor:119 [interfaces.py:start():190] Started network monitoring
|
269 |
+
2024-04-01 09:41:08,203 DEBUG SenderThread:119 [sender.py:send():378] send: config
|
270 |
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2024-04-01 09:41:08,205 DEBUG SenderThread:119 [sender.py:send():378] send: metric
|
271 |
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2024-04-01 09:41:08,205 DEBUG SenderThread:119 [sender.py:send():378] send: metric
|
272 |
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2024-04-01 09:41:08,205 WARNING SenderThread:119 [sender.py:send_metric():1316] Seen metric with glob (shouldn't happen)
|
273 |
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2024-04-01 09:41:09,833 INFO Thread-12 :119 [dir_watcher.py:_on_file_modified():288] file/dir modified: /kaggle/working/wandb/run-20240401_093743-ie4jv7u5/files/output.log
|
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2024-04-01 09:41:10,104 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
|
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2024-04-01 09:41:12,205 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: status_report
|
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2024-04-01 09:41:12,441 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: pause
|
277 |
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2024-04-01 09:41:12,442 INFO HandlerThread:119 [handler.py:handle_request_pause():708] stopping system metrics thread
|
278 |
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2024-04-01 09:41:12,442 INFO HandlerThread:119 [system_monitor.py:finish():203] Stopping system monitor
|
279 |
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2024-04-01 09:41:12,442 DEBUG SystemMonitor:119 [system_monitor.py:_start():172] Starting system metrics aggregation loop
|
280 |
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2024-04-01 09:41:12,442 DEBUG SystemMonitor:119 [system_monitor.py:_start():179] Finished system metrics aggregation loop
|
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2024-04-01 09:41:12,443 INFO HandlerThread:119 [interfaces.py:finish():202] Joined cpu monitor
|
282 |
+
2024-04-01 09:41:12,443 DEBUG SystemMonitor:119 [system_monitor.py:_start():183] Publishing last batch of metrics
|
283 |
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2024-04-01 09:41:12,443 INFO HandlerThread:119 [interfaces.py:finish():202] Joined disk monitor
|
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2024-04-01 09:41:12,454 INFO HandlerThread:119 [interfaces.py:finish():202] Joined gpu monitor
|
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+
2024-04-01 09:41:12,455 INFO HandlerThread:119 [interfaces.py:finish():202] Joined memory monitor
|
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+
2024-04-01 09:41:12,455 INFO HandlerThread:119 [interfaces.py:finish():202] Joined network monitor
|
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+
2024-04-01 09:41:12,455 DEBUG SenderThread:119 [sender.py:send():378] send: stats
|
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2024-04-01 09:41:15,105 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
|
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2024-04-01 09:41:17,461 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: status_report
|
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2024-04-01 09:41:17,836 INFO Thread-12 :119 [dir_watcher.py:_on_file_modified():288] file/dir modified: /kaggle/working/wandb/run-20240401_093743-ie4jv7u5/files/config.yaml
|
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2024-04-01 09:41:20,106 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
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2024-04-01 09:41:22,548 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: status_report
|
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2024-04-01 09:41:25,108 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
|
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2024-04-01 09:41:27,549 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: status_report
|
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2024-04-01 09:41:30,109 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
|
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2024-04-01 09:41:30,403 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: resume
|
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2024-04-01 09:41:30,403 INFO HandlerThread:119 [handler.py:handle_request_resume():699] starting system metrics thread
|
298 |
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2024-04-01 09:41:30,403 INFO HandlerThread:119 [system_monitor.py:start():194] Starting system monitor
|
299 |
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2024-04-01 09:41:30,403 INFO SystemMonitor:119 [system_monitor.py:_start():158] Starting system asset monitoring threads
|
300 |
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2024-04-01 09:41:30,404 INFO SystemMonitor:119 [interfaces.py:start():190] Started cpu monitoring
|
301 |
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2024-04-01 09:41:30,405 INFO SystemMonitor:119 [interfaces.py:start():190] Started disk monitoring
|
302 |
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2024-04-01 09:41:30,405 INFO SystemMonitor:119 [interfaces.py:start():190] Started gpu monitoring
|
303 |
+
2024-04-01 09:41:30,406 INFO SystemMonitor:119 [interfaces.py:start():190] Started memory monitoring
|
304 |
+
2024-04-01 09:41:30,406 INFO SystemMonitor:119 [interfaces.py:start():190] Started network monitoring
|
305 |
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2024-04-01 09:41:30,410 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: pause
|
306 |
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2024-04-01 09:41:30,410 INFO HandlerThread:119 [handler.py:handle_request_pause():708] stopping system metrics thread
|
307 |
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2024-04-01 09:41:30,410 INFO HandlerThread:119 [system_monitor.py:finish():203] Stopping system monitor
|
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2024-04-01 09:41:30,411 INFO HandlerThread:119 [interfaces.py:finish():202] Joined cpu monitor
|
309 |
+
2024-04-01 09:41:30,411 DEBUG SystemMonitor:119 [system_monitor.py:_start():172] Starting system metrics aggregation loop
|
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+
2024-04-01 09:41:30,411 INFO HandlerThread:119 [interfaces.py:finish():202] Joined disk monitor
|
311 |
+
2024-04-01 09:41:30,411 DEBUG SystemMonitor:119 [system_monitor.py:_start():179] Finished system metrics aggregation loop
|
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+
2024-04-01 09:41:30,412 DEBUG SystemMonitor:119 [system_monitor.py:_start():183] Publishing last batch of metrics
|
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2024-04-01 09:41:30,428 INFO HandlerThread:119 [interfaces.py:finish():202] Joined gpu monitor
|
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+
2024-04-01 09:41:30,429 INFO HandlerThread:119 [interfaces.py:finish():202] Joined memory monitor
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2024-04-01 09:41:30,429 INFO HandlerThread:119 [interfaces.py:finish():202] Joined network monitor
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2024-04-01 09:41:30,429 DEBUG SenderThread:119 [sender.py:send():378] send: stats
|
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2024-04-01 09:41:30,807 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: resume
|
318 |
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2024-04-01 09:41:30,807 INFO HandlerThread:119 [handler.py:handle_request_resume():699] starting system metrics thread
|
319 |
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2024-04-01 09:41:30,807 INFO HandlerThread:119 [system_monitor.py:start():194] Starting system monitor
|
320 |
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2024-04-01 09:41:30,807 INFO SystemMonitor:119 [system_monitor.py:_start():158] Starting system asset monitoring threads
|
321 |
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2024-04-01 09:41:30,808 INFO SystemMonitor:119 [interfaces.py:start():190] Started cpu monitoring
|
322 |
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2024-04-01 09:41:30,809 INFO SystemMonitor:119 [interfaces.py:start():190] Started disk monitoring
|
323 |
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2024-04-01 09:41:30,809 INFO SystemMonitor:119 [interfaces.py:start():190] Started gpu monitoring
|
324 |
+
2024-04-01 09:41:30,810 INFO SystemMonitor:119 [interfaces.py:start():190] Started memory monitoring
|
325 |
+
2024-04-01 09:41:30,812 INFO SystemMonitor:119 [interfaces.py:start():190] Started network monitoring
|
326 |
+
2024-04-01 09:41:31,309 DEBUG SenderThread:119 [sender.py:send():378] send: config
|
327 |
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2024-04-01 09:41:31,310 DEBUG SenderThread:119 [sender.py:send():378] send: metric
|
328 |
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2024-04-01 09:41:31,310 DEBUG SenderThread:119 [sender.py:send():378] send: metric
|
329 |
+
2024-04-01 09:41:31,310 WARNING SenderThread:119 [sender.py:send_metric():1316] Seen metric with glob (shouldn't happen)
|
330 |
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2024-04-01 09:41:33,311 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: status_report
|
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2024-04-01 09:41:35,240 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
|
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2024-04-01 09:41:35,576 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: pause
|
333 |
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2024-04-01 09:41:35,577 INFO HandlerThread:119 [handler.py:handle_request_pause():708] stopping system metrics thread
|
334 |
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2024-04-01 09:41:35,577 INFO HandlerThread:119 [system_monitor.py:finish():203] Stopping system monitor
|
335 |
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2024-04-01 09:41:35,577 DEBUG SystemMonitor:119 [system_monitor.py:_start():172] Starting system metrics aggregation loop
|
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2024-04-01 09:41:35,577 INFO HandlerThread:119 [interfaces.py:finish():202] Joined cpu monitor
|
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2024-04-01 09:41:35,578 DEBUG SystemMonitor:119 [system_monitor.py:_start():179] Finished system metrics aggregation loop
|
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2024-04-01 09:41:35,578 DEBUG SystemMonitor:119 [system_monitor.py:_start():183] Publishing last batch of metrics
|
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2024-04-01 09:41:35,578 INFO HandlerThread:119 [interfaces.py:finish():202] Joined disk monitor
|
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2024-04-01 09:41:35,590 INFO HandlerThread:119 [interfaces.py:finish():202] Joined gpu monitor
|
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2024-04-01 09:41:35,590 INFO HandlerThread:119 [interfaces.py:finish():202] Joined memory monitor
|
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2024-04-01 09:41:35,590 INFO HandlerThread:119 [interfaces.py:finish():202] Joined network monitor
|
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2024-04-01 09:41:35,591 DEBUG SenderThread:119 [sender.py:send():378] send: stats
|
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2024-04-01 09:41:38,591 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: status_report
|
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2024-04-01 09:41:40,242 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
|
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2024-04-01 09:41:43,592 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: status_report
|
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2024-04-01 09:41:45,080 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: resume
|
348 |
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2024-04-01 09:41:45,081 INFO HandlerThread:119 [handler.py:handle_request_resume():699] starting system metrics thread
|
349 |
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2024-04-01 09:41:45,081 INFO HandlerThread:119 [system_monitor.py:start():194] Starting system monitor
|
350 |
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2024-04-01 09:41:45,081 INFO SystemMonitor:119 [system_monitor.py:_start():158] Starting system asset monitoring threads
|
351 |
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2024-04-01 09:41:45,081 INFO SystemMonitor:119 [interfaces.py:start():190] Started cpu monitoring
|
352 |
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2024-04-01 09:41:45,082 INFO SystemMonitor:119 [interfaces.py:start():190] Started disk monitoring
|
353 |
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2024-04-01 09:41:45,084 INFO SystemMonitor:119 [interfaces.py:start():190] Started gpu monitoring
|
354 |
+
2024-04-01 09:41:45,084 INFO SystemMonitor:119 [interfaces.py:start():190] Started memory monitoring
|
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2024-04-01 09:41:45,085 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: pause
|
356 |
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2024-04-01 09:41:45,085 INFO HandlerThread:119 [handler.py:handle_request_pause():708] stopping system metrics thread
|
357 |
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2024-04-01 09:41:45,085 INFO SystemMonitor:119 [interfaces.py:start():190] Started network monitoring
|
358 |
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2024-04-01 09:41:45,085 INFO HandlerThread:119 [system_monitor.py:finish():203] Stopping system monitor
|
359 |
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2024-04-01 09:41:45,086 DEBUG SystemMonitor:119 [system_monitor.py:_start():172] Starting system metrics aggregation loop
|
360 |
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2024-04-01 09:41:45,087 DEBUG SystemMonitor:119 [system_monitor.py:_start():179] Finished system metrics aggregation loop
|
361 |
+
2024-04-01 09:41:45,087 DEBUG SystemMonitor:119 [system_monitor.py:_start():183] Publishing last batch of metrics
|
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2024-04-01 09:41:48,754 INFO SystemMonitor:119 [interfaces.py:start():190] Started cpu monitoring
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2024-04-01 09:41:49,283 WARNING SenderThread:119 [sender.py:send_metric():1316] Seen metric with glob (shouldn't happen)
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2024-04-01 09:42:48,757 DEBUG SystemMonitor:119 [system_monitor.py:_start():172] Starting system metrics aggregation loop
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2024-04-01 09:42:59,875 INFO Thread-12 :119 [dir_watcher.py:_on_file_modified():288] file/dir modified: /kaggle/working/wandb/run-20240401_093743-ie4jv7u5/files/wandb-summary.json
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2024-04-01 09:43:44,292 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: partial_history
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2024-04-01 09:43:44,294 DEBUG SenderThread:119 [sender.py:send():378] send: history
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2024-04-01 09:43:44,296 INFO SenderThread:119 [sender.py:_save_file():1365] saving file wandb-summary.json with policy end
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2024-04-01 09:43:44,893 INFO Thread-12 :119 [dir_watcher.py:_on_file_modified():288] file/dir modified: /kaggle/working/wandb/run-20240401_093743-ie4jv7u5/files/wandb-summary.json
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2024-04-01 09:43:45,272 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
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2024-04-01 09:43:48,760 DEBUG SenderThread:119 [sender.py:send():378] send: stats
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2024-04-01 09:43:57,624 INFO SenderThread:119 [sender.py:_save_file():1365] saving file wandb-summary.json with policy end
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2024-04-01 09:43:57,898 INFO Thread-12 :119 [dir_watcher.py:_on_file_modified():288] file/dir modified: /kaggle/working/wandb/run-20240401_093743-ie4jv7u5/files/wandb-summary.json
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2024-04-01 09:43:59,490 INFO SenderThread:119 [sender.py:_save_file():1365] saving file wandb-summary.json with policy end
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2024-04-01 09:44:00,275 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
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2024-04-01 09:44:11,311 INFO SenderThread:119 [sender.py:_save_file():1365] saving file wandb-summary.json with policy end
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2024-04-01 09:44:13,133 INFO SenderThread:119 [sender.py:_save_file():1365] saving file wandb-summary.json with policy end
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2024-04-01 09:44:13,903 INFO Thread-12 :119 [dir_watcher.py:_on_file_modified():288] file/dir modified: /kaggle/working/wandb/run-20240401_093743-ie4jv7u5/files/wandb-summary.json
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2024-04-01 09:44:16,334 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: status_report
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2024-04-01 09:44:24,824 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: partial_history
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2024-04-01 09:44:24,825 DEBUG SenderThread:119 [sender.py:send():378] send: history
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2024-04-01 09:44:24,826 DEBUG SenderThread:119 [sender.py:send_request():405] send_request: summary_record
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2024-04-01 09:44:24,826 INFO SenderThread:119 [sender.py:_save_file():1365] saving file wandb-summary.json with policy end
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2024-04-01 09:44:24,907 INFO Thread-12 :119 [dir_watcher.py:_on_file_modified():288] file/dir modified: /kaggle/working/wandb/run-20240401_093743-ie4jv7u5/files/wandb-summary.json
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2024-04-01 09:44:25,280 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
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2024-04-01 09:44:26,645 DEBUG SenderThread:119 [sender.py:send():378] send: history
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2024-04-01 09:44:26,646 INFO SenderThread:119 [sender.py:_save_file():1365] saving file wandb-summary.json with policy end
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2024-04-01 09:44:26,848 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: status_report
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2024-04-01 09:44:26,908 INFO Thread-12 :119 [dir_watcher.py:_on_file_modified():288] file/dir modified: /kaggle/working/wandb/run-20240401_093743-ie4jv7u5/files/wandb-summary.json
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2024-04-01 09:44:29,909 INFO Thread-12 :119 [dir_watcher.py:_on_file_modified():288] file/dir modified: /kaggle/working/wandb/run-20240401_093743-ie4jv7u5/files/output.log
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2024-04-01 09:44:30,281 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
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2024-04-01 09:44:39,730 INFO SenderThread:119 [sender.py:_save_file():1365] saving file wandb-summary.json with policy end
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2024-04-01 09:44:39,912 INFO Thread-12 :119 [dir_watcher.py:_on_file_modified():288] file/dir modified: /kaggle/working/wandb/run-20240401_093743-ie4jv7u5/files/wandb-summary.json
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2024-04-01 09:44:40,283 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
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2024-04-01 09:44:41,562 DEBUG SenderThread:119 [sender.py:send():378] send: history
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|
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2024-04-01 09:44:41,562 INFO SenderThread:119 [sender.py:_save_file():1365] saving file wandb-summary.json with policy end
|
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2024-04-01 09:44:41,913 INFO Thread-12 :119 [dir_watcher.py:_on_file_modified():288] file/dir modified: /kaggle/working/wandb/run-20240401_093743-ie4jv7u5/files/wandb-summary.json
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2024-04-01 09:44:42,764 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: status_report
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2024-04-01 09:44:43,914 INFO Thread-12 :119 [dir_watcher.py:_on_file_modified():288] file/dir modified: /kaggle/working/wandb/run-20240401_093743-ie4jv7u5/files/output.log
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2024-04-01 09:44:45,284 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
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2024-04-01 09:44:47,765 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: status_report
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2024-04-01 09:44:48,762 DEBUG SenderThread:119 [sender.py:send():378] send: stats
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2024-04-01 09:44:50,285 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
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2024-04-01 09:44:51,614 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: pause
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2024-04-01 09:44:51,614 INFO HandlerThread:119 [handler.py:handle_request_pause():708] stopping system metrics thread
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596 |
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597 |
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598 |
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2024-04-01 09:44:51,615 DEBUG SystemMonitor:119 [system_monitor.py:_start():179] Finished system metrics aggregation loop
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599 |
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2024-04-01 09:44:51,615 INFO HandlerThread:119 [interfaces.py:finish():202] Joined disk monitor
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600 |
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2024-04-01 09:44:51,616 DEBUG SystemMonitor:119 [system_monitor.py:_start():183] Publishing last batch of metrics
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601 |
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2024-04-01 09:44:51,627 INFO HandlerThread:119 [interfaces.py:finish():202] Joined gpu monitor
|
602 |
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2024-04-01 09:44:51,627 INFO HandlerThread:119 [interfaces.py:finish():202] Joined memory monitor
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603 |
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2024-04-01 09:44:51,627 INFO HandlerThread:119 [interfaces.py:finish():202] Joined network monitor
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604 |
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2024-04-01 09:44:51,628 DEBUG SenderThread:119 [sender.py:send():378] send: stats
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605 |
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2024-04-01 09:44:53,628 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: status_report
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2024-04-01 09:44:55,287 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
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2024-04-01 09:44:58,630 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: status_report
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2024-04-01 09:45:00,288 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
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2024-04-01 09:45:03,631 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: status_report
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2024-04-01 09:45:05,289 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
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2024-04-01 09:45:08,631 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: status_report
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2024-04-01 09:45:10,291 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
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2024-04-01 09:45:13,632 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: status_report
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2024-04-01 09:45:15,292 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
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2024-04-01 09:45:20,293 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
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2024-04-01 09:45:25,294 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
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619 |
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2024-04-01 09:45:28,635 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: status_report
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622 |
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2024-04-01 09:45:32,016 INFO HandlerThread:119 [handler.py:handle_request_resume():699] starting system metrics thread
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623 |
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2024-04-01 09:45:32,016 INFO HandlerThread:119 [system_monitor.py:start():194] Starting system monitor
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624 |
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2024-04-01 09:45:32,016 INFO SystemMonitor:119 [system_monitor.py:_start():158] Starting system asset monitoring threads
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625 |
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2024-04-01 09:45:32,016 INFO SystemMonitor:119 [interfaces.py:start():190] Started cpu monitoring
|
626 |
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2024-04-01 09:45:32,019 INFO SystemMonitor:119 [interfaces.py:start():190] Started disk monitoring
|
627 |
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2024-04-01 09:45:32,019 INFO SystemMonitor:119 [interfaces.py:start():190] Started gpu monitoring
|
628 |
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2024-04-01 09:45:32,020 INFO SystemMonitor:119 [interfaces.py:start():190] Started memory monitoring
|
629 |
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2024-04-01 09:45:32,023 INFO SystemMonitor:119 [interfaces.py:start():190] Started network monitoring
|
630 |
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2024-04-01 09:45:32,039 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: pause
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631 |
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2024-04-01 09:45:32,040 INFO HandlerThread:119 [handler.py:handle_request_pause():708] stopping system metrics thread
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632 |
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633 |
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634 |
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2024-04-01 09:45:32,040 DEBUG SystemMonitor:119 [system_monitor.py:_start():179] Finished system metrics aggregation loop
|
635 |
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2024-04-01 09:45:32,040 DEBUG SystemMonitor:119 [system_monitor.py:_start():183] Publishing last batch of metrics
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636 |
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2024-04-01 09:45:32,040 INFO HandlerThread:119 [interfaces.py:finish():202] Joined cpu monitor
|
637 |
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2024-04-01 09:45:32,041 INFO HandlerThread:119 [interfaces.py:finish():202] Joined disk monitor
|
638 |
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2024-04-01 09:45:32,055 INFO HandlerThread:119 [interfaces.py:finish():202] Joined gpu monitor
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639 |
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2024-04-01 09:45:32,055 INFO HandlerThread:119 [interfaces.py:finish():202] Joined memory monitor
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640 |
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2024-04-01 09:45:32,055 INFO HandlerThread:119 [interfaces.py:finish():202] Joined network monitor
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641 |
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2024-04-01 09:45:32,055 DEBUG SenderThread:119 [sender.py:send():378] send: stats
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642 |
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2024-04-01 09:45:35,296 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
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644 |
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2024-04-01 09:45:40,298 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
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2024-04-01 09:45:45,299 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
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2024-04-01 09:45:50,299 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
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2024-04-01 09:45:54,060 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: status_report
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2024-04-01 09:45:54,718 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: resume
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652 |
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2024-04-01 09:45:54,718 INFO HandlerThread:119 [handler.py:handle_request_resume():699] starting system metrics thread
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653 |
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2024-04-01 09:45:54,718 INFO HandlerThread:119 [system_monitor.py:start():194] Starting system monitor
|
654 |
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2024-04-01 09:45:54,718 INFO SystemMonitor:119 [system_monitor.py:_start():158] Starting system asset monitoring threads
|
655 |
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2024-04-01 09:45:54,719 INFO SystemMonitor:119 [interfaces.py:start():190] Started cpu monitoring
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656 |
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2024-04-01 09:45:54,719 INFO SystemMonitor:119 [interfaces.py:start():190] Started disk monitoring
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657 |
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2024-04-01 09:45:54,720 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: pause
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658 |
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2024-04-01 09:45:54,720 INFO SystemMonitor:119 [interfaces.py:start():190] Started gpu monitoring
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659 |
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2024-04-01 09:45:54,720 INFO HandlerThread:119 [handler.py:handle_request_pause():708] stopping system metrics thread
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660 |
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2024-04-01 09:45:54,721 INFO SystemMonitor:119 [interfaces.py:start():190] Started memory monitoring
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661 |
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2024-04-01 09:45:54,721 INFO HandlerThread:119 [system_monitor.py:finish():203] Stopping system monitor
|
662 |
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2024-04-01 09:45:54,722 INFO SystemMonitor:119 [interfaces.py:start():190] Started network monitoring
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663 |
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2024-04-01 09:45:54,722 DEBUG SystemMonitor:119 [system_monitor.py:_start():172] Starting system metrics aggregation loop
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664 |
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2024-04-01 09:45:54,722 DEBUG SystemMonitor:119 [system_monitor.py:_start():179] Finished system metrics aggregation loop
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665 |
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2024-04-01 09:45:54,722 DEBUG SystemMonitor:119 [system_monitor.py:_start():183] Publishing last batch of metrics
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666 |
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2024-04-01 09:45:54,725 INFO HandlerThread:119 [interfaces.py:finish():202] Joined cpu monitor
|
667 |
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2024-04-01 09:45:54,727 INFO HandlerThread:119 [interfaces.py:finish():202] Joined disk monitor
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668 |
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2024-04-01 09:45:54,747 INFO HandlerThread:119 [interfaces.py:finish():202] Joined gpu monitor
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669 |
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2024-04-01 09:45:54,747 INFO HandlerThread:119 [interfaces.py:finish():202] Joined memory monitor
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670 |
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2024-04-01 09:45:54,747 INFO HandlerThread:119 [interfaces.py:finish():202] Joined network monitor
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2024-04-01 09:45:54,747 DEBUG SenderThread:119 [sender.py:send():378] send: stats
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2024-04-01 09:45:55,301 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
|
673 |
+
2024-04-01 09:45:57,946 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: resume
|
674 |
+
2024-04-01 09:45:57,946 INFO HandlerThread:119 [handler.py:handle_request_resume():699] starting system metrics thread
|
675 |
+
2024-04-01 09:45:57,946 INFO HandlerThread:119 [system_monitor.py:start():194] Starting system monitor
|
676 |
+
2024-04-01 09:45:57,947 INFO SystemMonitor:119 [system_monitor.py:_start():158] Starting system asset monitoring threads
|
677 |
+
2024-04-01 09:45:57,947 INFO SystemMonitor:119 [interfaces.py:start():190] Started cpu monitoring
|
678 |
+
2024-04-01 09:45:57,948 INFO SystemMonitor:119 [interfaces.py:start():190] Started disk monitoring
|
679 |
+
2024-04-01 09:45:57,950 INFO SystemMonitor:119 [interfaces.py:start():190] Started gpu monitoring
|
680 |
+
2024-04-01 09:45:57,951 INFO SystemMonitor:119 [interfaces.py:start():190] Started memory monitoring
|
681 |
+
2024-04-01 09:45:57,951 INFO SystemMonitor:119 [interfaces.py:start():190] Started network monitoring
|
682 |
+
2024-04-01 09:45:59,749 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: status_report
|
683 |
+
2024-04-01 09:46:00,302 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
|
684 |
+
2024-04-01 09:46:04,750 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: status_report
|
685 |
+
2024-04-01 09:46:05,303 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
|
686 |
+
2024-04-01 09:46:09,751 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: status_report
|
687 |
+
2024-04-01 09:46:10,304 DEBUG HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
|
wandb/run-20240401_093743-ie4jv7u5/logs/debug.log
ADDED
@@ -0,0 +1,68 @@
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1 |
+
2024-04-01 09:37:43,078 INFO MainThread:34 [wandb_setup.py:_flush():76] Current SDK version is 0.16.4
|
2 |
+
2024-04-01 09:37:43,078 INFO MainThread:34 [wandb_setup.py:_flush():76] Configure stats pid to 34
|
3 |
+
2024-04-01 09:37:43,078 INFO MainThread:34 [wandb_setup.py:_flush():76] Loading settings from /root/.config/wandb/settings
|
4 |
+
2024-04-01 09:37:43,078 INFO MainThread:34 [wandb_setup.py:_flush():76] Loading settings from /kaggle/working/wandb/settings
|
5 |
+
2024-04-01 09:37:43,078 INFO MainThread:34 [wandb_setup.py:_flush():76] Loading settings from environment variables: {}
|
6 |
+
2024-04-01 09:37:43,078 INFO MainThread:34 [wandb_setup.py:_flush():76] Applying setup settings: {'_disable_service': False}
|
7 |
+
2024-04-01 09:37:43,078 INFO MainThread:34 [wandb_setup.py:_flush():76] Inferring run settings from compute environment: {'program': '<python with no main file>'}
|
8 |
+
2024-04-01 09:37:43,078 INFO MainThread:34 [wandb_setup.py:_flush():76] Applying login settings: {'api_key': '***REDACTED***'}
|
9 |
+
2024-04-01 09:37:43,078 INFO MainThread:34 [wandb_init.py:_log_setup():526] Logging user logs to /kaggle/working/wandb/run-20240401_093743-ie4jv7u5/logs/debug.log
|
10 |
+
2024-04-01 09:37:43,078 INFO MainThread:34 [wandb_init.py:_log_setup():527] Logging internal logs to /kaggle/working/wandb/run-20240401_093743-ie4jv7u5/logs/debug-internal.log
|
11 |
+
2024-04-01 09:37:43,078 INFO MainThread:34 [wandb_init.py:_jupyter_setup():472] configuring jupyter hooks <wandb.sdk.wandb_init._WandbInit object at 0x7e30ad2cb760>
|
12 |
+
2024-04-01 09:37:43,079 INFO MainThread:34 [wandb_init.py:init():566] calling init triggers
|
13 |
+
2024-04-01 09:37:43,079 INFO MainThread:34 [wandb_init.py:init():573] wandb.init called with sweep_config: {}
|
14 |
+
config: {}
|
15 |
+
2024-04-01 09:37:43,079 INFO MainThread:34 [wandb_init.py:init():616] starting backend
|
16 |
+
2024-04-01 09:37:43,079 INFO MainThread:34 [wandb_init.py:init():620] setting up manager
|
17 |
+
2024-04-01 09:37:43,081 INFO MainThread:34 [backend.py:_multiprocessing_setup():105] multiprocessing start_methods=fork,spawn,forkserver, using: spawn
|
18 |
+
2024-04-01 09:37:43,085 INFO MainThread:34 [wandb_init.py:init():628] backend started and connected
|
19 |
+
2024-04-01 09:37:43,097 INFO MainThread:34 [wandb_run.py:_label_probe_notebook():1295] probe notebook
|
20 |
+
2024-04-01 09:37:43,596 INFO MainThread:34 [wandb_init.py:init():720] updated telemetry
|
21 |
+
2024-04-01 09:37:43,599 INFO MainThread:34 [wandb_init.py:init():753] communicating run to backend with 90.0 second timeout
|
22 |
+
2024-04-01 09:37:43,765 INFO MainThread:34 [wandb_run.py:_on_init():2262] communicating current version
|
23 |
+
2024-04-01 09:37:43,855 INFO MainThread:34 [wandb_run.py:_on_init():2271] got version response upgrade_message: "wandb version 0.16.5 is available! To upgrade, please run:\n $ pip install wandb --upgrade"
|
24 |
+
|
25 |
+
2024-04-01 09:37:43,855 INFO MainThread:34 [wandb_init.py:init():804] starting run threads in backend
|
26 |
+
2024-04-01 09:38:14,888 INFO MainThread:34 [wandb_run.py:_console_start():2241] atexit reg
|
27 |
+
2024-04-01 09:38:14,889 INFO MainThread:34 [wandb_run.py:_redirect():2096] redirect: wrap_raw
|
28 |
+
2024-04-01 09:38:14,889 INFO MainThread:34 [wandb_run.py:_redirect():2161] Wrapping output streams.
|
29 |
+
2024-04-01 09:38:14,889 INFO MainThread:34 [wandb_run.py:_redirect():2186] Redirects installed.
|
30 |
+
2024-04-01 09:38:14,891 INFO MainThread:34 [wandb_init.py:init():847] run started, returning control to user process
|
31 |
+
2024-04-01 09:38:14,896 INFO MainThread:34 [wandb_run.py:_config_callback():1343] config_cb None None {'vocab_size': 32000, 'max_position_embeddings': 32768, 'hidden_size': 4096, 'intermediate_size': 14336, 'num_hidden_layers': 32, 'num_attention_heads': 32, 'sliding_window': None, 'num_key_value_heads': 8, 'hidden_act': 'silu', 'initializer_range': 0.02, 'rms_norm_eps': 1e-05, 'use_cache': False, 'rope_theta': 1000000.0, 'attention_dropout': 0.0, 'return_dict': True, 'output_hidden_states': False, 'output_attentions': False, 'torchscript': False, 'torch_dtype': 'bfloat16', 'use_bfloat16': False, 'tf_legacy_loss': False, 'pruned_heads': {}, 'tie_word_embeddings': False, 'chunk_size_feed_forward': 0, 'is_encoder_decoder': False, 'is_decoder': False, 'cross_attention_hidden_size': None, 'add_cross_attention': False, 'tie_encoder_decoder': False, 'max_length': 20, 'min_length': 0, 'do_sample': False, 'early_stopping': False, 'num_beams': 1, 'num_beam_groups': 1, 'diversity_penalty': 0.0, 'temperature': 1.0, 'top_k': 50, 'top_p': 1.0, 'typical_p': 1.0, 'repetition_penalty': 1.0, 'length_penalty': 1.0, 'no_repeat_ngram_size': 0, 'encoder_no_repeat_ngram_size': 0, 'bad_words_ids': None, 'num_return_sequences': 1, 'output_scores': False, 'return_dict_in_generate': False, 'forced_bos_token_id': None, 'forced_eos_token_id': None, 'remove_invalid_values': False, 'exponential_decay_length_penalty': None, 'suppress_tokens': None, 'begin_suppress_tokens': None, 'architectures': ['MistralForCausalLM'], 'finetuning_task': None, 'id2label': {0: 'LABEL_0', 1: 'LABEL_1'}, 'label2id': {'LABEL_0': 0, 'LABEL_1': 1}, 'tokenizer_class': None, 'prefix': None, 'bos_token_id': 1, 'pad_token_id': 0, 'eos_token_id': 2, 'sep_token_id': None, 'decoder_start_token_id': None, 'task_specific_params': None, 'problem_type': None, '_name_or_path': 'TheBloke/Mistral-7B-Instruct-v0.2-GPTQ', 'transformers_version': '4.38.2', 'model_type': 'mistral', 'pretraining_tp': 1, 'quantization_config': {'quant_method': 'QuantizationMethod.GPTQ', 'bits': 4, 'tokenizer': None, 'dataset': None, 'group_size': 128, 'damp_percent': 0.1, 'desc_act': True, 'sym': True, 'true_sequential': True, 'use_cuda_fp16': False, 'model_seqlen': None, 'block_name_to_quantize': None, 'module_name_preceding_first_block': None, 'batch_size': 1, 'pad_token_id': None, 'use_exllama': True, 'max_input_length': None, 'exllama_config': {'version': 'ExllamaVersion.ONE'}, 'cache_block_outputs': True, 'modules_in_block_to_quantize': None}, 'output_dir': '/kaggle/working/', 'overwrite_output_dir': False, 'do_train': False, 'do_eval': True, 'do_predict': False, 'evaluation_strategy': 'epoch', 'prediction_loss_only': False, 'per_device_train_batch_size': 6, 'per_device_eval_batch_size': 6, 'per_gpu_train_batch_size': None, 'per_gpu_eval_batch_size': None, 'gradient_accumulation_steps': 4, 'eval_accumulation_steps': None, 'eval_delay': 0, 'learning_rate': 0.0002, 'weight_decay': 0.01, 'adam_beta1': 0.9, 'adam_beta2': 0.999, 'adam_epsilon': 1e-08, 'max_grad_norm': 1.0, 'num_train_epochs': 30, 'max_steps': -1, 'lr_scheduler_type': 'linear', 'lr_scheduler_kwargs': {}, 'warmup_ratio': 0.0, 'warmup_steps': 2, 'log_level': 'passive', 'log_level_replica': 'warning', 'log_on_each_node': True, 'logging_dir': '/kaggle/working/runs/Apr01_09-37-28_148e249fd8ed', 'logging_strategy': 'epoch', 'logging_first_step': False, 'logging_steps': 500, 'logging_nan_inf_filter': True, 'save_strategy': 'epoch', 'save_steps': 500, 'save_total_limit': None, 'save_safetensors': True, 'save_on_each_node': False, 'save_only_model': False, 'no_cuda': False, 'use_cpu': False, 'use_mps_device': False, 'seed': 42, 'data_seed': None, 'jit_mode_eval': False, 'use_ipex': False, 'bf16': False, 'fp16': True, 'fp16_opt_level': 'O1', 'half_precision_backend': 'auto', 'bf16_full_eval': False, 'fp16_full_eval': False, 'tf32': None, 'local_rank': 0, 'ddp_backend': None, 'tpu_num_cores': None, 'tpu_metrics_debug': False, 'debug': [], 'dataloader_drop_last': False, 'eval_steps': None, 'dataloader_num_workers': 0, 'dataloader_prefetch_factor': None, 'past_index': -1, 'run_name': '/kaggle/working/', 'disable_tqdm': False, 'remove_unused_columns': True, 'label_names': None, 'load_best_model_at_end': True, 'metric_for_best_model': 'loss', 'greater_is_better': False, 'ignore_data_skip': False, 'fsdp': [], 'fsdp_min_num_params': 0, 'fsdp_config': {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}, 'fsdp_transformer_layer_cls_to_wrap': None, 'accelerator_config': {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True}, 'deepspeed': None, 'label_smoothing_factor': 0.0, 'optim': 'paged_adamw_8bit', 'optim_args': None, 'adafactor': False, 'group_by_length': False, 'length_column_name': 'length', 'report_to': ['tensorboard', 'wandb'], 'ddp_find_unused_parameters': None, 'ddp_bucket_cap_mb': None, 'ddp_broadcast_buffers': None, 'dataloader_pin_memory': True, 'dataloader_persistent_workers': False, 'skip_memory_metrics': True, 'use_legacy_prediction_loop': False, 'push_to_hub': False, 'resume_from_checkpoint': None, 'hub_model_id': None, 'hub_strategy': 'every_save', 'hub_token': '<HUB_TOKEN>', 'hub_private_repo': False, 'hub_always_push': False, 'gradient_checkpointing': False, 'gradient_checkpointing_kwargs': None, 'include_inputs_for_metrics': False, 'fp16_backend': 'auto', 'push_to_hub_model_id': None, 'push_to_hub_organization': None, 'push_to_hub_token': '<PUSH_TO_HUB_TOKEN>', 'mp_parameters': '', 'auto_find_batch_size': False, 'full_determinism': False, 'torchdynamo': None, 'ray_scope': 'last', 'ddp_timeout': 1800, 'torch_compile': False, 'torch_compile_backend': None, 'torch_compile_mode': None, 'dispatch_batches': None, 'split_batches': None, 'include_tokens_per_second': False, 'include_num_input_tokens_seen': False, 'neftune_noise_alpha': None}
|
32 |
+
2024-04-01 09:38:55,054 INFO MainThread:34 [jupyter.py:save_ipynb():373] not saving jupyter notebook
|
33 |
+
2024-04-01 09:38:55,054 INFO MainThread:34 [wandb_init.py:_pause_backend():437] pausing backend
|
34 |
+
2024-04-01 09:39:21,055 INFO MainThread:34 [wandb_init.py:_resume_backend():442] resuming backend
|
35 |
+
2024-04-01 09:39:21,061 INFO MainThread:34 [jupyter.py:save_ipynb():373] not saving jupyter notebook
|
36 |
+
2024-04-01 09:39:21,061 INFO MainThread:34 [wandb_init.py:_pause_backend():437] pausing backend
|
37 |
+
2024-04-01 09:39:21,457 INFO MainThread:34 [wandb_init.py:_resume_backend():442] resuming backend
|
38 |
+
2024-04-01 09:39:22,007 INFO MainThread:34 [wandb_run.py:_config_callback():1343] config_cb None None {'vocab_size': 32000, 'max_position_embeddings': 32768, 'hidden_size': 4096, 'intermediate_size': 14336, 'num_hidden_layers': 32, 'num_attention_heads': 32, 'sliding_window': None, 'num_key_value_heads': 8, 'hidden_act': 'silu', 'initializer_range': 0.02, 'rms_norm_eps': 1e-05, 'use_cache': False, 'rope_theta': 1000000.0, 'attention_dropout': 0.0, 'return_dict': True, 'output_hidden_states': False, 'output_attentions': False, 'torchscript': False, 'torch_dtype': 'bfloat16', 'use_bfloat16': False, 'tf_legacy_loss': False, 'pruned_heads': {}, 'tie_word_embeddings': False, 'chunk_size_feed_forward': 0, 'is_encoder_decoder': False, 'is_decoder': False, 'cross_attention_hidden_size': None, 'add_cross_attention': False, 'tie_encoder_decoder': False, 'max_length': 20, 'min_length': 0, 'do_sample': False, 'early_stopping': False, 'num_beams': 1, 'num_beam_groups': 1, 'diversity_penalty': 0.0, 'temperature': 1.0, 'top_k': 50, 'top_p': 1.0, 'typical_p': 1.0, 'repetition_penalty': 1.0, 'length_penalty': 1.0, 'no_repeat_ngram_size': 0, 'encoder_no_repeat_ngram_size': 0, 'bad_words_ids': None, 'num_return_sequences': 1, 'output_scores': False, 'return_dict_in_generate': False, 'forced_bos_token_id': None, 'forced_eos_token_id': None, 'remove_invalid_values': False, 'exponential_decay_length_penalty': None, 'suppress_tokens': None, 'begin_suppress_tokens': None, 'architectures': ['MistralForCausalLM'], 'finetuning_task': None, 'id2label': {0: 'LABEL_0', 1: 'LABEL_1'}, 'label2id': {'LABEL_0': 0, 'LABEL_1': 1}, 'tokenizer_class': None, 'prefix': None, 'bos_token_id': 1, 'pad_token_id': 0, 'eos_token_id': 2, 'sep_token_id': None, 'decoder_start_token_id': None, 'task_specific_params': None, 'problem_type': None, '_name_or_path': 'TheBloke/Mistral-7B-Instruct-v0.2-GPTQ', 'transformers_version': '4.38.2', 'model_type': 'mistral', 'pretraining_tp': 1, 'quantization_config': {'quant_method': 'QuantizationMethod.GPTQ', 'bits': 4, 'tokenizer': None, 'dataset': None, 'group_size': 128, 'damp_percent': 0.1, 'desc_act': True, 'sym': True, 'true_sequential': True, 'use_cuda_fp16': False, 'model_seqlen': None, 'block_name_to_quantize': None, 'module_name_preceding_first_block': None, 'batch_size': 1, 'pad_token_id': None, 'use_exllama': True, 'max_input_length': None, 'exllama_config': {'version': 'ExllamaVersion.ONE'}, 'cache_block_outputs': True, 'modules_in_block_to_quantize': None}, 'output_dir': '/kaggle/working/', 'overwrite_output_dir': False, 'do_train': False, 'do_eval': True, 'do_predict': False, 'evaluation_strategy': 'epoch', 'prediction_loss_only': False, 'per_device_train_batch_size': 6, 'per_device_eval_batch_size': 6, 'per_gpu_train_batch_size': None, 'per_gpu_eval_batch_size': None, 'gradient_accumulation_steps': 4, 'eval_accumulation_steps': None, 'eval_delay': 0, 'learning_rate': 0.0002, 'weight_decay': 0.01, 'adam_beta1': 0.9, 'adam_beta2': 0.999, 'adam_epsilon': 1e-08, 'max_grad_norm': 1.0, 'num_train_epochs': 50, 'max_steps': -1, 'lr_scheduler_type': 'linear', 'lr_scheduler_kwargs': {}, 'warmup_ratio': 0.0, 'warmup_steps': 2, 'log_level': 'passive', 'log_level_replica': 'warning', 'log_on_each_node': True, 'logging_dir': '/kaggle/working/runs/Apr01_09-39-21_148e249fd8ed', 'logging_strategy': 'epoch', 'logging_first_step': False, 'logging_steps': 500, 'logging_nan_inf_filter': True, 'save_strategy': 'epoch', 'save_steps': 500, 'save_total_limit': None, 'save_safetensors': True, 'save_on_each_node': False, 'save_only_model': False, 'no_cuda': False, 'use_cpu': False, 'use_mps_device': False, 'seed': 42, 'data_seed': None, 'jit_mode_eval': False, 'use_ipex': False, 'bf16': False, 'fp16': True, 'fp16_opt_level': 'O1', 'half_precision_backend': 'auto', 'bf16_full_eval': False, 'fp16_full_eval': False, 'tf32': None, 'local_rank': 0, 'ddp_backend': None, 'tpu_num_cores': None, 'tpu_metrics_debug': False, 'debug': [], 'dataloader_drop_last': False, 'eval_steps': None, 'dataloader_num_workers': 0, 'dataloader_prefetch_factor': None, 'past_index': -1, 'run_name': '/kaggle/working/', 'disable_tqdm': False, 'remove_unused_columns': True, 'label_names': None, 'load_best_model_at_end': True, 'metric_for_best_model': 'loss', 'greater_is_better': False, 'ignore_data_skip': False, 'fsdp': [], 'fsdp_min_num_params': 0, 'fsdp_config': {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}, 'fsdp_transformer_layer_cls_to_wrap': None, 'accelerator_config': {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True}, 'deepspeed': None, 'label_smoothing_factor': 0.0, 'optim': 'paged_adamw_8bit', 'optim_args': None, 'adafactor': False, 'group_by_length': False, 'length_column_name': 'length', 'report_to': ['tensorboard', 'wandb'], 'ddp_find_unused_parameters': None, 'ddp_bucket_cap_mb': None, 'ddp_broadcast_buffers': None, 'dataloader_pin_memory': True, 'dataloader_persistent_workers': False, 'skip_memory_metrics': True, 'use_legacy_prediction_loop': False, 'push_to_hub': False, 'resume_from_checkpoint': None, 'hub_model_id': None, 'hub_strategy': 'every_save', 'hub_token': '<HUB_TOKEN>', 'hub_private_repo': False, 'hub_always_push': False, 'gradient_checkpointing': False, 'gradient_checkpointing_kwargs': None, 'include_inputs_for_metrics': False, 'fp16_backend': 'auto', 'push_to_hub_model_id': None, 'push_to_hub_organization': None, 'push_to_hub_token': '<PUSH_TO_HUB_TOKEN>', 'mp_parameters': '', 'auto_find_batch_size': False, 'full_determinism': False, 'torchdynamo': None, 'ray_scope': 'last', 'ddp_timeout': 1800, 'torch_compile': False, 'torch_compile_backend': None, 'torch_compile_mode': None, 'dispatch_batches': None, 'split_batches': None, 'include_tokens_per_second': False, 'include_num_input_tokens_seen': False, 'neftune_noise_alpha': None}
|
39 |
+
2024-04-01 09:39:59,405 INFO MainThread:34 [jupyter.py:save_ipynb():373] not saving jupyter notebook
|
40 |
+
2024-04-01 09:39:59,405 INFO MainThread:34 [wandb_init.py:_pause_backend():437] pausing backend
|
41 |
+
2024-04-01 09:41:00,163 INFO MainThread:34 [wandb_init.py:_resume_backend():442] resuming backend
|
42 |
+
2024-04-01 09:41:00,169 INFO MainThread:34 [jupyter.py:save_ipynb():373] not saving jupyter notebook
|
43 |
+
2024-04-01 09:41:00,169 INFO MainThread:34 [wandb_init.py:_pause_backend():437] pausing backend
|
44 |
+
2024-04-01 09:41:07,654 INFO MainThread:34 [wandb_init.py:_resume_backend():442] resuming backend
|
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2024-04-01 09:41:08,198 INFO MainThread:34 [wandb_run.py:_config_callback():1343] config_cb None None {'vocab_size': 32000, 'max_position_embeddings': 32768, 'hidden_size': 4096, 'intermediate_size': 14336, 'num_hidden_layers': 32, 'num_attention_heads': 32, 'sliding_window': None, 'num_key_value_heads': 8, 'hidden_act': 'silu', 'initializer_range': 0.02, 'rms_norm_eps': 1e-05, 'use_cache': False, 'rope_theta': 1000000.0, 'attention_dropout': 0.0, 'return_dict': True, 'output_hidden_states': False, 'output_attentions': False, 'torchscript': False, 'torch_dtype': 'bfloat16', 'use_bfloat16': False, 'tf_legacy_loss': False, 'pruned_heads': {}, 'tie_word_embeddings': False, 'chunk_size_feed_forward': 0, 'is_encoder_decoder': False, 'is_decoder': False, 'cross_attention_hidden_size': None, 'add_cross_attention': False, 'tie_encoder_decoder': False, 'max_length': 20, 'min_length': 0, 'do_sample': False, 'early_stopping': False, 'num_beams': 1, 'num_beam_groups': 1, 'diversity_penalty': 0.0, 'temperature': 1.0, 'top_k': 50, 'top_p': 1.0, 'typical_p': 1.0, 'repetition_penalty': 1.0, 'length_penalty': 1.0, 'no_repeat_ngram_size': 0, 'encoder_no_repeat_ngram_size': 0, 'bad_words_ids': None, 'num_return_sequences': 1, 'output_scores': False, 'return_dict_in_generate': False, 'forced_bos_token_id': None, 'forced_eos_token_id': None, 'remove_invalid_values': False, 'exponential_decay_length_penalty': None, 'suppress_tokens': None, 'begin_suppress_tokens': None, 'architectures': ['MistralForCausalLM'], 'finetuning_task': None, 'id2label': {0: 'LABEL_0', 1: 'LABEL_1'}, 'label2id': {'LABEL_0': 0, 'LABEL_1': 1}, 'tokenizer_class': None, 'prefix': None, 'bos_token_id': 1, 'pad_token_id': 0, 'eos_token_id': 2, 'sep_token_id': None, 'decoder_start_token_id': None, 'task_specific_params': None, 'problem_type': None, '_name_or_path': 'TheBloke/Mistral-7B-Instruct-v0.2-GPTQ', 'transformers_version': '4.38.2', 'model_type': 'mistral', 'pretraining_tp': 1, 'quantization_config': {'quant_method': 'QuantizationMethod.GPTQ', 'bits': 4, 'tokenizer': None, 'dataset': None, 'group_size': 128, 'damp_percent': 0.1, 'desc_act': True, 'sym': True, 'true_sequential': True, 'use_cuda_fp16': False, 'model_seqlen': None, 'block_name_to_quantize': None, 'module_name_preceding_first_block': None, 'batch_size': 1, 'pad_token_id': None, 'use_exllama': True, 'max_input_length': None, 'exllama_config': {'version': 'ExllamaVersion.ONE'}, 'cache_block_outputs': True, 'modules_in_block_to_quantize': None}, 'output_dir': '/kaggle/working/', 'overwrite_output_dir': False, 'do_train': False, 'do_eval': True, 'do_predict': False, 'evaluation_strategy': 'epoch', 'prediction_loss_only': False, 'per_device_train_batch_size': 2, 'per_device_eval_batch_size': 2, 'per_gpu_train_batch_size': None, 'per_gpu_eval_batch_size': None, 'gradient_accumulation_steps': 4, 'eval_accumulation_steps': None, 'eval_delay': 0, 'learning_rate': 0.0002, 'weight_decay': 0.01, 'adam_beta1': 0.9, 'adam_beta2': 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2024-04-01 09:41:31,300 INFO MainThread:34 [wandb_run.py:_config_callback():1343] config_cb None None {'vocab_size': 32000, 'max_position_embeddings': 32768, 'hidden_size': 4096, 'intermediate_size': 14336, 'num_hidden_layers': 32, 'num_attention_heads': 32, 'sliding_window': None, 'num_key_value_heads': 8, 'hidden_act': 'silu', 'initializer_range': 0.02, 'rms_norm_eps': 1e-05, 'use_cache': False, 'rope_theta': 1000000.0, 'attention_dropout': 0.0, 'return_dict': True, 'output_hidden_states': False, 'output_attentions': False, 'torchscript': False, 'torch_dtype': 'bfloat16', 'use_bfloat16': False, 'tf_legacy_loss': False, 'pruned_heads': {}, 'tie_word_embeddings': False, 'chunk_size_feed_forward': 0, 'is_encoder_decoder': False, 'is_decoder': False, 'cross_attention_hidden_size': None, 'add_cross_attention': False, 'tie_encoder_decoder': False, 'max_length': 20, 'min_length': 0, 'do_sample': False, 'early_stopping': False, 'num_beams': 1, 'num_beam_groups': 1, 'diversity_penalty': 0.0, 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'dataloader_pin_memory': True, 'dataloader_persistent_workers': False, 'skip_memory_metrics': True, 'use_legacy_prediction_loop': False, 'push_to_hub': False, 'resume_from_checkpoint': None, 'hub_model_id': None, 'hub_strategy': 'every_save', 'hub_token': '<HUB_TOKEN>', 'hub_private_repo': False, 'hub_always_push': False, 'gradient_checkpointing': False, 'gradient_checkpointing_kwargs': None, 'include_inputs_for_metrics': False, 'fp16_backend': 'auto', 'push_to_hub_model_id': None, 'push_to_hub_organization': None, 'push_to_hub_token': '<PUSH_TO_HUB_TOKEN>', 'mp_parameters': '', 'auto_find_batch_size': False, 'full_determinism': False, 'torchdynamo': None, 'ray_scope': 'last', 'ddp_timeout': 1800, 'torch_compile': False, 'torch_compile_backend': None, 'torch_compile_mode': None, 'dispatch_batches': None, 'split_batches': None, 'include_tokens_per_second': False, 'include_num_input_tokens_seen': False, 'neftune_noise_alpha': None}
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2024-04-01 09:41:49,276 INFO MainThread:34 [wandb_run.py:_config_callback():1343] config_cb None None {'vocab_size': 32000, 'max_position_embeddings': 32768, 'hidden_size': 4096, 'intermediate_size': 14336, 'num_hidden_layers': 32, 'num_attention_heads': 32, 'sliding_window': None, 'num_key_value_heads': 8, 'hidden_act': 'silu', 'initializer_range': 0.02, 'rms_norm_eps': 1e-05, 'use_cache': False, 'rope_theta': 1000000.0, 'attention_dropout': 0.0, 'return_dict': True, 'output_hidden_states': False, 'output_attentions': False, 'torchscript': False, 'torch_dtype': 'bfloat16', 'use_bfloat16': False, 'tf_legacy_loss': False, 'pruned_heads': {}, 'tie_word_embeddings': False, 'chunk_size_feed_forward': 0, 'is_encoder_decoder': False, 'is_decoder': False, 'cross_attention_hidden_size': None, 'add_cross_attention': False, 'tie_encoder_decoder': False, 'max_length': 20, 'min_length': 0, 'do_sample': False, 'early_stopping': False, 'num_beams': 1, 'num_beam_groups': 1, 'diversity_penalty': 0.0, 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