Upload folder using huggingface_hub
Browse files- README.md +110 -0
- adapter_config.json +28 -0
- adapter_model.bin +3 -0
- checkpoint-1002/README.md +219 -0
- checkpoint-1002/adapter_config.json +28 -0
- checkpoint-1002/adapter_model.bin +3 -0
- checkpoint-1002/optimizer.pt +3 -0
- checkpoint-1002/rng_state.pth +3 -0
- checkpoint-1002/scheduler.pt +3 -0
- checkpoint-1002/trainer_state.json +0 -0
- checkpoint-1002/training_args.bin +3 -0
- checkpoint-334/README.md +219 -0
- checkpoint-334/adapter_config.json +28 -0
- checkpoint-334/adapter_model.bin +3 -0
- checkpoint-334/optimizer.pt +3 -0
- checkpoint-334/rng_state.pth +3 -0
- checkpoint-334/scheduler.pt +3 -0
- checkpoint-334/trainer_state.json +2151 -0
- checkpoint-334/training_args.bin +3 -0
- checkpoint-668/README.md +219 -0
- checkpoint-668/adapter_config.json +28 -0
- checkpoint-668/adapter_model.bin +3 -0
- checkpoint-668/optimizer.pt +3 -0
- checkpoint-668/rng_state.pth +3 -0
- checkpoint-668/scheduler.pt +3 -0
- checkpoint-668/trainer_state.json +4291 -0
- checkpoint-668/training_args.bin +3 -0
- config.json +40 -0
- special_tokens_map.json +24 -0
- tokenizer.model +3 -0
- tokenizer_config.json +44 -0
README.md
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---
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license: apache-2.0
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base_model: mistralai/Mistral-7B-v0.1
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tags:
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- generated_from_trainer
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model-index:
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- name: qlora-out
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
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# qlora-out
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This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5631
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0004
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- train_batch_size: 2
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- eval_batch_size: 2
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 8
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 300
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- num_epochs: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 0.8335 | 0.06 | 20 | 0.6429 |
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| 0.6725 | 0.12 | 40 | 0.5888 |
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| 0.5927 | 0.18 | 60 | 0.5603 |
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| 0.5847 | 0.24 | 80 | 0.5362 |
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| 0.5552 | 0.3 | 100 | 0.5256 |
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| 0.5511 | 0.36 | 120 | 0.5243 |
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| 0.5466 | 0.42 | 140 | 0.5102 |
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| 0.4395 | 0.48 | 160 | 0.5065 |
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| 0.6854 | 0.54 | 180 | 0.4971 |
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| 0.7326 | 0.6 | 200 | 0.5150 |
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| 0.8204 | 0.66 | 220 | 0.5008 |
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| 0.6009 | 0.72 | 240 | 0.4972 |
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| 0.4471 | 0.78 | 260 | 0.4944 |
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| 0.5934 | 0.84 | 280 | 0.5146 |
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| 0.6574 | 0.9 | 300 | 0.5057 |
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| 0.4566 | 0.96 | 320 | 0.4880 |
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| 0.6119 | 1.02 | 340 | 0.5442 |
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| 0.3779 | 1.08 | 360 | 0.5540 |
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| 0.4431 | 1.14 | 380 | 0.5375 |
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| 0.38 | 1.2 | 400 | 0.5541 |
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| 0.4542 | 1.26 | 420 | 0.5359 |
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| 0.5392 | 1.32 | 440 | 0.5394 |
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| 0.2573 | 1.38 | 460 | 0.5318 |
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| 0.5441 | 1.44 | 480 | 0.5201 |
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| 0.3758 | 1.5 | 500 | 0.5147 |
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| 0.4403 | 1.56 | 520 | 0.5134 |
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| 0.3308 | 1.62 | 540 | 0.5289 |
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| 0.4604 | 1.68 | 560 | 0.5205 |
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| 0.4479 | 1.74 | 580 | 0.5340 |
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| 0.521 | 1.8 | 600 | 0.5094 |
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| 0.32 | 1.86 | 620 | 0.4995 |
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| 0.3984 | 1.92 | 640 | 0.4878 |
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| 0.3799 | 1.98 | 660 | 0.4826 |
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| 0.1484 | 2.04 | 680 | 0.7261 |
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| 0.3305 | 2.1 | 700 | 0.6187 |
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| 0.1477 | 2.16 | 720 | 0.5499 |
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| 0.176 | 2.22 | 740 | 0.5796 |
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| 0.1892 | 2.28 | 760 | 0.5717 |
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| 0.1921 | 2.34 | 780 | 0.5416 |
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| 0.1366 | 2.4 | 800 | 0.5866 |
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| 0.1726 | 2.46 | 820 | 0.5562 |
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| 0.1264 | 2.51 | 840 | 0.5621 |
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| 0.2054 | 2.57 | 860 | 0.5678 |
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| 0.1722 | 2.63 | 880 | 0.5573 |
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| 0.2399 | 2.69 | 900 | 0.5553 |
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| 0.229 | 2.75 | 920 | 0.5565 |
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| 0.1876 | 2.81 | 940 | 0.5609 |
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| 0.2281 | 2.87 | 960 | 0.5633 |
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| 0.1727 | 2.93 | 980 | 0.5645 |
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| 0.3536 | 2.99 | 1000 | 0.5631 |
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### Framework versions
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- Transformers 4.34.1
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.6
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- Tokenizers 0.14.1
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adapter_config.json
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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": "mistralai/Mistral-7B-v0.1",
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"bias": "none",
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"fan_in_fan_out": null,
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"inference_mode": true,
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"init_lora_weights": true,
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"layers_pattern": null,
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"layers_to_transform": null,
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"lora_alpha": 16,
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"lora_dropout": 0.05,
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"modules_to_save": null,
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"peft_type": "LORA",
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"r": 32,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"o_proj",
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"v_proj",
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"q_proj",
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"k_proj",
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"down_proj",
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"gate_proj",
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"up_proj"
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],
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"task_type": "CAUSAL_LM"
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}
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adapter_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:568c2437eeacd3b0544fb93db03ca0342cadf1f2adfd24db27db237d4430ace9
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size 335705741
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checkpoint-1002/README.md
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---
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library_name: peft
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base_model: mistralai/Mistral-7B-v0.1
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---
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# Model Card for Model ID
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<!-- Provide a quick summary of what the model is/does. -->
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## Model Details
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### Model Description
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<!-- Provide a longer summary of what this model is. -->
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- **Developed by:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Model type:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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- **Finetuned from model [optional]:** [More Information Needed]
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### Model Sources [optional]
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<!-- Provide the basic links for the model. -->
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- **Repository:** [More Information Needed]
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- **Paper [optional]:** [More Information Needed]
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- **Demo [optional]:** [More Information Needed]
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## Uses
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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### Direct Use
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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[More Information Needed]
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### Downstream Use [optional]
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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[More Information Needed]
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### Out-of-Scope Use
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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[More Information Needed]
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## Bias, Risks, and Limitations
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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[More Information Needed]
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### Recommendations
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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## How to Get Started with the Model
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Use the code below to get started with the model.
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[More Information Needed]
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## Training Details
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### Training Data
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<!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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[More Information Needed]
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### Training Procedure
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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#### Preprocessing [optional]
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[More Information Needed]
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#### Training Hyperparameters
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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#### Speeds, Sizes, Times [optional]
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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[More Information Needed]
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## Evaluation
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<!-- This section describes the evaluation protocols and provides the results. -->
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### Testing Data, Factors & Metrics
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#### Testing Data
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<!-- This should link to a Data Card if possible. -->
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[More Information Needed]
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#### Factors
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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[More Information Needed]
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#### Metrics
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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[More Information Needed]
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### Results
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[More Information Needed]
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+
#### Summary
|
131 |
+
|
132 |
+
|
133 |
+
|
134 |
+
## Model Examination [optional]
|
135 |
+
|
136 |
+
<!-- Relevant interpretability work for the model goes here -->
|
137 |
+
|
138 |
+
[More Information Needed]
|
139 |
+
|
140 |
+
## Environmental Impact
|
141 |
+
|
142 |
+
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
143 |
+
|
144 |
+
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
|
145 |
+
|
146 |
+
- **Hardware Type:** [More Information Needed]
|
147 |
+
- **Hours used:** [More Information Needed]
|
148 |
+
- **Cloud Provider:** [More Information Needed]
|
149 |
+
- **Compute Region:** [More Information Needed]
|
150 |
+
- **Carbon Emitted:** [More Information Needed]
|
151 |
+
|
152 |
+
## Technical Specifications [optional]
|
153 |
+
|
154 |
+
### Model Architecture and Objective
|
155 |
+
|
156 |
+
[More Information Needed]
|
157 |
+
|
158 |
+
### Compute Infrastructure
|
159 |
+
|
160 |
+
[More Information Needed]
|
161 |
+
|
162 |
+
#### Hardware
|
163 |
+
|
164 |
+
[More Information Needed]
|
165 |
+
|
166 |
+
#### Software
|
167 |
+
|
168 |
+
[More Information Needed]
|
169 |
+
|
170 |
+
## Citation [optional]
|
171 |
+
|
172 |
+
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
173 |
+
|
174 |
+
**BibTeX:**
|
175 |
+
|
176 |
+
[More Information Needed]
|
177 |
+
|
178 |
+
**APA:**
|
179 |
+
|
180 |
+
[More Information Needed]
|
181 |
+
|
182 |
+
## Glossary [optional]
|
183 |
+
|
184 |
+
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
185 |
+
|
186 |
+
[More Information Needed]
|
187 |
+
|
188 |
+
## More Information [optional]
|
189 |
+
|
190 |
+
[More Information Needed]
|
191 |
+
|
192 |
+
## Model Card Authors [optional]
|
193 |
+
|
194 |
+
[More Information Needed]
|
195 |
+
|
196 |
+
## Model Card Contact
|
197 |
+
|
198 |
+
[More Information Needed]
|
199 |
+
|
200 |
+
|
201 |
+
## Training procedure
|
202 |
+
|
203 |
+
|
204 |
+
The following `bitsandbytes` quantization config was used during training:
|
205 |
+
- quant_method: bitsandbytes
|
206 |
+
- load_in_8bit: False
|
207 |
+
- load_in_4bit: True
|
208 |
+
- llm_int8_threshold: 6.0
|
209 |
+
- llm_int8_skip_modules: None
|
210 |
+
- llm_int8_enable_fp32_cpu_offload: False
|
211 |
+
- llm_int8_has_fp16_weight: False
|
212 |
+
- bnb_4bit_quant_type: nf4
|
213 |
+
- bnb_4bit_use_double_quant: True
|
214 |
+
- bnb_4bit_compute_dtype: bfloat16
|
215 |
+
|
216 |
+
### Framework versions
|
217 |
+
|
218 |
+
|
219 |
+
- PEFT 0.6.0.dev0
|
checkpoint-1002/adapter_config.json
ADDED
@@ -0,0 +1,28 @@
|
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|
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|
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|
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|
|
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|
1 |
+
{
|
2 |
+
"alpha_pattern": {},
|
3 |
+
"auto_mapping": null,
|
4 |
+
"base_model_name_or_path": "mistralai/Mistral-7B-v0.1",
|
5 |
+
"bias": "none",
|
6 |
+
"fan_in_fan_out": null,
|
7 |
+
"inference_mode": true,
|
8 |
+
"init_lora_weights": true,
|
9 |
+
"layers_pattern": null,
|
10 |
+
"layers_to_transform": null,
|
11 |
+
"lora_alpha": 16,
|
12 |
+
"lora_dropout": 0.05,
|
13 |
+
"modules_to_save": null,
|
14 |
+
"peft_type": "LORA",
|
15 |
+
"r": 32,
|
16 |
+
"rank_pattern": {},
|
17 |
+
"revision": null,
|
18 |
+
"target_modules": [
|
19 |
+
"o_proj",
|
20 |
+
"v_proj",
|
21 |
+
"q_proj",
|
22 |
+
"k_proj",
|
23 |
+
"down_proj",
|
24 |
+
"gate_proj",
|
25 |
+
"up_proj"
|
26 |
+
],
|
27 |
+
"task_type": "CAUSAL_LM"
|
28 |
+
}
|
checkpoint-1002/adapter_model.bin
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
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2 |
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oid sha256:568c2437eeacd3b0544fb93db03ca0342cadf1f2adfd24db27db237d4430ace9
|
3 |
+
size 335705741
|
checkpoint-1002/optimizer.pt
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
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oid sha256:2b6d21da256d32fa5a4667d275880556615fedea0d3a40536f102ce1d2c3fc0e
|
3 |
+
size 671364101
|
checkpoint-1002/rng_state.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:6132062d501391cea8a366ab4456cfc242c24b5718df54b54e06fc9476b3306b
|
3 |
+
size 14575
|
checkpoint-1002/scheduler.pt
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:9918e5a7f1925ff5913d17bc9cb764150357ed8088ad5535a840dab9a4d9bca6
|
3 |
+
size 627
|
checkpoint-1002/trainer_state.json
ADDED
The diff for this file is too large to render.
See raw diff
|
|
checkpoint-1002/training_args.bin
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:437823b67a8e71dde1f898ebf1534afc55a51ee86d8735c8e1f03954c766c4a4
|
3 |
+
size 4475
|
checkpoint-334/README.md
ADDED
@@ -0,0 +1,219 @@
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
|
1 |
+
---
|
2 |
+
library_name: peft
|
3 |
+
base_model: mistralai/Mistral-7B-v0.1
|
4 |
+
---
|
5 |
+
|
6 |
+
# Model Card for Model ID
|
7 |
+
|
8 |
+
<!-- Provide a quick summary of what the model is/does. -->
|
9 |
+
|
10 |
+
|
11 |
+
|
12 |
+
## Model Details
|
13 |
+
|
14 |
+
### Model Description
|
15 |
+
|
16 |
+
<!-- Provide a longer summary of what this model is. -->
|
17 |
+
|
18 |
+
|
19 |
+
|
20 |
+
- **Developed by:** [More Information Needed]
|
21 |
+
- **Shared by [optional]:** [More Information Needed]
|
22 |
+
- **Model type:** [More Information Needed]
|
23 |
+
- **Language(s) (NLP):** [More Information Needed]
|
24 |
+
- **License:** [More Information Needed]
|
25 |
+
- **Finetuned from model [optional]:** [More Information Needed]
|
26 |
+
|
27 |
+
### Model Sources [optional]
|
28 |
+
|
29 |
+
<!-- Provide the basic links for the model. -->
|
30 |
+
|
31 |
+
- **Repository:** [More Information Needed]
|
32 |
+
- **Paper [optional]:** [More Information Needed]
|
33 |
+
- **Demo [optional]:** [More Information Needed]
|
34 |
+
|
35 |
+
## Uses
|
36 |
+
|
37 |
+
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
38 |
+
|
39 |
+
### Direct Use
|
40 |
+
|
41 |
+
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
42 |
+
|
43 |
+
[More Information Needed]
|
44 |
+
|
45 |
+
### Downstream Use [optional]
|
46 |
+
|
47 |
+
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
48 |
+
|
49 |
+
[More Information Needed]
|
50 |
+
|
51 |
+
### Out-of-Scope Use
|
52 |
+
|
53 |
+
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
54 |
+
|
55 |
+
[More Information Needed]
|
56 |
+
|
57 |
+
## Bias, Risks, and Limitations
|
58 |
+
|
59 |
+
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
60 |
+
|
61 |
+
[More Information Needed]
|
62 |
+
|
63 |
+
### Recommendations
|
64 |
+
|
65 |
+
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
|
66 |
+
|
67 |
+
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
|
68 |
+
|
69 |
+
## How to Get Started with the Model
|
70 |
+
|
71 |
+
Use the code below to get started with the model.
|
72 |
+
|
73 |
+
[More Information Needed]
|
74 |
+
|
75 |
+
## Training Details
|
76 |
+
|
77 |
+
### Training Data
|
78 |
+
|
79 |
+
<!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
|
80 |
+
|
81 |
+
[More Information Needed]
|
82 |
+
|
83 |
+
### Training Procedure
|
84 |
+
|
85 |
+
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
|
86 |
+
|
87 |
+
#### Preprocessing [optional]
|
88 |
+
|
89 |
+
[More Information Needed]
|
90 |
+
|
91 |
+
|
92 |
+
#### Training Hyperparameters
|
93 |
+
|
94 |
+
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
|
95 |
+
|
96 |
+
#### Speeds, Sizes, Times [optional]
|
97 |
+
|
98 |
+
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
99 |
+
|
100 |
+
[More Information Needed]
|
101 |
+
|
102 |
+
## Evaluation
|
103 |
+
|
104 |
+
<!-- This section describes the evaluation protocols and provides the results. -->
|
105 |
+
|
106 |
+
### Testing Data, Factors & Metrics
|
107 |
+
|
108 |
+
#### Testing Data
|
109 |
+
|
110 |
+
<!-- This should link to a Data Card if possible. -->
|
111 |
+
|
112 |
+
[More Information Needed]
|
113 |
+
|
114 |
+
#### Factors
|
115 |
+
|
116 |
+
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
117 |
+
|
118 |
+
[More Information Needed]
|
119 |
+
|
120 |
+
#### Metrics
|
121 |
+
|
122 |
+
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
123 |
+
|
124 |
+
[More Information Needed]
|
125 |
+
|
126 |
+
### Results
|
127 |
+
|
128 |
+
[More Information Needed]
|
129 |
+
|
130 |
+
#### Summary
|
131 |
+
|
132 |
+
|
133 |
+
|
134 |
+
## Model Examination [optional]
|
135 |
+
|
136 |
+
<!-- Relevant interpretability work for the model goes here -->
|
137 |
+
|
138 |
+
[More Information Needed]
|
139 |
+
|
140 |
+
## Environmental Impact
|
141 |
+
|
142 |
+
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
143 |
+
|
144 |
+
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
|
145 |
+
|
146 |
+
- **Hardware Type:** [More Information Needed]
|
147 |
+
- **Hours used:** [More Information Needed]
|
148 |
+
- **Cloud Provider:** [More Information Needed]
|
149 |
+
- **Compute Region:** [More Information Needed]
|
150 |
+
- **Carbon Emitted:** [More Information Needed]
|
151 |
+
|
152 |
+
## Technical Specifications [optional]
|
153 |
+
|
154 |
+
### Model Architecture and Objective
|
155 |
+
|
156 |
+
[More Information Needed]
|
157 |
+
|
158 |
+
### Compute Infrastructure
|
159 |
+
|
160 |
+
[More Information Needed]
|
161 |
+
|
162 |
+
#### Hardware
|
163 |
+
|
164 |
+
[More Information Needed]
|
165 |
+
|
166 |
+
#### Software
|
167 |
+
|
168 |
+
[More Information Needed]
|
169 |
+
|
170 |
+
## Citation [optional]
|
171 |
+
|
172 |
+
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
173 |
+
|
174 |
+
**BibTeX:**
|
175 |
+
|
176 |
+
[More Information Needed]
|
177 |
+
|
178 |
+
**APA:**
|
179 |
+
|
180 |
+
[More Information Needed]
|
181 |
+
|
182 |
+
## Glossary [optional]
|
183 |
+
|
184 |
+
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
185 |
+
|
186 |
+
[More Information Needed]
|
187 |
+
|
188 |
+
## More Information [optional]
|
189 |
+
|
190 |
+
[More Information Needed]
|
191 |
+
|
192 |
+
## Model Card Authors [optional]
|
193 |
+
|
194 |
+
[More Information Needed]
|
195 |
+
|
196 |
+
## Model Card Contact
|
197 |
+
|
198 |
+
[More Information Needed]
|
199 |
+
|
200 |
+
|
201 |
+
## Training procedure
|
202 |
+
|
203 |
+
|
204 |
+
The following `bitsandbytes` quantization config was used during training:
|
205 |
+
- quant_method: bitsandbytes
|
206 |
+
- load_in_8bit: False
|
207 |
+
- load_in_4bit: True
|
208 |
+
- llm_int8_threshold: 6.0
|
209 |
+
- llm_int8_skip_modules: None
|
210 |
+
- llm_int8_enable_fp32_cpu_offload: False
|
211 |
+
- llm_int8_has_fp16_weight: False
|
212 |
+
- bnb_4bit_quant_type: nf4
|
213 |
+
- bnb_4bit_use_double_quant: True
|
214 |
+
- bnb_4bit_compute_dtype: bfloat16
|
215 |
+
|
216 |
+
### Framework versions
|
217 |
+
|
218 |
+
|
219 |
+
- PEFT 0.6.0.dev0
|
checkpoint-334/adapter_config.json
ADDED
@@ -0,0 +1,28 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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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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|
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|
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|
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|
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|
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|
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|
16 |
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|
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|
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|
19 |
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|
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|
21 |
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|
22 |
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|
23 |
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|
24 |
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|
25 |
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|
26 |
+
],
|
27 |
+
"task_type": "CAUSAL_LM"
|
28 |
+
}
|
checkpoint-334/adapter_model.bin
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version https://git-lfs.github.com/spec/v1
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size 671364101
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checkpoint-334/rng_state.pth
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version https://git-lfs.github.com/spec/v1
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size 14575
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checkpoint-334/scheduler.pt
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version https://git-lfs.github.com/spec/v1
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size 627
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checkpoint-334/trainer_state.json
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---
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2 |
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library_name: peft
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3 |
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base_model: mistralai/Mistral-7B-v0.1
|
4 |
+
---
|
5 |
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6 |
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# Model Card for Model ID
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7 |
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|
8 |
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<!-- Provide a quick summary of what the model is/does. -->
|
9 |
+
|
10 |
+
|
11 |
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|
12 |
+
## Model Details
|
13 |
+
|
14 |
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### Model Description
|
15 |
+
|
16 |
+
<!-- Provide a longer summary of what this model is. -->
|
17 |
+
|
18 |
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|
19 |
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20 |
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- **Developed by:** [More Information Needed]
|
21 |
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- **Shared by [optional]:** [More Information Needed]
|
22 |
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- **Model type:** [More Information Needed]
|
23 |
+
- **Language(s) (NLP):** [More Information Needed]
|
24 |
+
- **License:** [More Information Needed]
|
25 |
+
- **Finetuned from model [optional]:** [More Information Needed]
|
26 |
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|
27 |
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### Model Sources [optional]
|
28 |
+
|
29 |
+
<!-- Provide the basic links for the model. -->
|
30 |
+
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31 |
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- **Repository:** [More Information Needed]
|
32 |
+
- **Paper [optional]:** [More Information Needed]
|
33 |
+
- **Demo [optional]:** [More Information Needed]
|
34 |
+
|
35 |
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## Uses
|
36 |
+
|
37 |
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
38 |
+
|
39 |
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### Direct Use
|
40 |
+
|
41 |
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
42 |
+
|
43 |
+
[More Information Needed]
|
44 |
+
|
45 |
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### Downstream Use [optional]
|
46 |
+
|
47 |
+
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
48 |
+
|
49 |
+
[More Information Needed]
|
50 |
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|
51 |
+
### Out-of-Scope Use
|
52 |
+
|
53 |
+
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
54 |
+
|
55 |
+
[More Information Needed]
|
56 |
+
|
57 |
+
## Bias, Risks, and Limitations
|
58 |
+
|
59 |
+
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
60 |
+
|
61 |
+
[More Information Needed]
|
62 |
+
|
63 |
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### Recommendations
|
64 |
+
|
65 |
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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66 |
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|
67 |
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
|
68 |
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|
69 |
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## How to Get Started with the Model
|
70 |
+
|
71 |
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Use the code below to get started with the model.
|
72 |
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|
73 |
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[More Information Needed]
|
74 |
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|
75 |
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## Training Details
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76 |
+
|
77 |
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### Training Data
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78 |
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79 |
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<!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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80 |
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[More Information Needed]
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82 |
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### Training Procedure
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84 |
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85 |
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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#### Preprocessing [optional]
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88 |
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89 |
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[More Information Needed]
|
90 |
+
|
91 |
+
|
92 |
+
#### Training Hyperparameters
|
93 |
+
|
94 |
+
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
|
95 |
+
|
96 |
+
#### Speeds, Sizes, Times [optional]
|
97 |
+
|
98 |
+
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
99 |
+
|
100 |
+
[More Information Needed]
|
101 |
+
|
102 |
+
## Evaluation
|
103 |
+
|
104 |
+
<!-- This section describes the evaluation protocols and provides the results. -->
|
105 |
+
|
106 |
+
### Testing Data, Factors & Metrics
|
107 |
+
|
108 |
+
#### Testing Data
|
109 |
+
|
110 |
+
<!-- This should link to a Data Card if possible. -->
|
111 |
+
|
112 |
+
[More Information Needed]
|
113 |
+
|
114 |
+
#### Factors
|
115 |
+
|
116 |
+
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
117 |
+
|
118 |
+
[More Information Needed]
|
119 |
+
|
120 |
+
#### Metrics
|
121 |
+
|
122 |
+
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
123 |
+
|
124 |
+
[More Information Needed]
|
125 |
+
|
126 |
+
### Results
|
127 |
+
|
128 |
+
[More Information Needed]
|
129 |
+
|
130 |
+
#### Summary
|
131 |
+
|
132 |
+
|
133 |
+
|
134 |
+
## Model Examination [optional]
|
135 |
+
|
136 |
+
<!-- Relevant interpretability work for the model goes here -->
|
137 |
+
|
138 |
+
[More Information Needed]
|
139 |
+
|
140 |
+
## Environmental Impact
|
141 |
+
|
142 |
+
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
143 |
+
|
144 |
+
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
|
145 |
+
|
146 |
+
- **Hardware Type:** [More Information Needed]
|
147 |
+
- **Hours used:** [More Information Needed]
|
148 |
+
- **Cloud Provider:** [More Information Needed]
|
149 |
+
- **Compute Region:** [More Information Needed]
|
150 |
+
- **Carbon Emitted:** [More Information Needed]
|
151 |
+
|
152 |
+
## Technical Specifications [optional]
|
153 |
+
|
154 |
+
### Model Architecture and Objective
|
155 |
+
|
156 |
+
[More Information Needed]
|
157 |
+
|
158 |
+
### Compute Infrastructure
|
159 |
+
|
160 |
+
[More Information Needed]
|
161 |
+
|
162 |
+
#### Hardware
|
163 |
+
|
164 |
+
[More Information Needed]
|
165 |
+
|
166 |
+
#### Software
|
167 |
+
|
168 |
+
[More Information Needed]
|
169 |
+
|
170 |
+
## Citation [optional]
|
171 |
+
|
172 |
+
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
173 |
+
|
174 |
+
**BibTeX:**
|
175 |
+
|
176 |
+
[More Information Needed]
|
177 |
+
|
178 |
+
**APA:**
|
179 |
+
|
180 |
+
[More Information Needed]
|
181 |
+
|
182 |
+
## Glossary [optional]
|
183 |
+
|
184 |
+
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
185 |
+
|
186 |
+
[More Information Needed]
|
187 |
+
|
188 |
+
## More Information [optional]
|
189 |
+
|
190 |
+
[More Information Needed]
|
191 |
+
|
192 |
+
## Model Card Authors [optional]
|
193 |
+
|
194 |
+
[More Information Needed]
|
195 |
+
|
196 |
+
## Model Card Contact
|
197 |
+
|
198 |
+
[More Information Needed]
|
199 |
+
|
200 |
+
|
201 |
+
## Training procedure
|
202 |
+
|
203 |
+
|
204 |
+
The following `bitsandbytes` quantization config was used during training:
|
205 |
+
- quant_method: bitsandbytes
|
206 |
+
- load_in_8bit: False
|
207 |
+
- load_in_4bit: True
|
208 |
+
- llm_int8_threshold: 6.0
|
209 |
+
- llm_int8_skip_modules: None
|
210 |
+
- llm_int8_enable_fp32_cpu_offload: False
|
211 |
+
- llm_int8_has_fp16_weight: False
|
212 |
+
- bnb_4bit_quant_type: nf4
|
213 |
+
- bnb_4bit_use_double_quant: True
|
214 |
+
- bnb_4bit_compute_dtype: bfloat16
|
215 |
+
|
216 |
+
### Framework versions
|
217 |
+
|
218 |
+
|
219 |
+
- PEFT 0.6.0.dev0
|
checkpoint-668/adapter_config.json
ADDED
@@ -0,0 +1,28 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
|
|
|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"alpha_pattern": {},
|
3 |
+
"auto_mapping": null,
|
4 |
+
"base_model_name_or_path": "mistralai/Mistral-7B-v0.1",
|
5 |
+
"bias": "none",
|
6 |
+
"fan_in_fan_out": null,
|
7 |
+
"inference_mode": true,
|
8 |
+
"init_lora_weights": true,
|
9 |
+
"layers_pattern": null,
|
10 |
+
"layers_to_transform": null,
|
11 |
+
"lora_alpha": 16,
|
12 |
+
"lora_dropout": 0.05,
|
13 |
+
"modules_to_save": null,
|
14 |
+
"peft_type": "LORA",
|
15 |
+
"r": 32,
|
16 |
+
"rank_pattern": {},
|
17 |
+
"revision": null,
|
18 |
+
"target_modules": [
|
19 |
+
"o_proj",
|
20 |
+
"v_proj",
|
21 |
+
"q_proj",
|
22 |
+
"k_proj",
|
23 |
+
"down_proj",
|
24 |
+
"gate_proj",
|
25 |
+
"up_proj"
|
26 |
+
],
|
27 |
+
"task_type": "CAUSAL_LM"
|
28 |
+
}
|
checkpoint-668/adapter_model.bin
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:9c18bcb71d4eb4db3d371f982e40c6464027fa7dcee7078cd5ce04872b4c14c8
|
3 |
+
size 335705741
|
checkpoint-668/optimizer.pt
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:4caf0bf32c1a2d0004f7b3a64a4a59368f9738bcaa9f49243bec4e120c0a2adc
|
3 |
+
size 671364101
|
checkpoint-668/rng_state.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:8edc689b4e667096ce9f1321230458cf516e583142069fb7ce01188cc266c8b5
|
3 |
+
size 14575
|
checkpoint-668/scheduler.pt
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:3206f15c7d9ecd7446f3de714be42999153b81a96f79b5bbedecb40eef013d8c
|
3 |
+
size 627
|
checkpoint-668/trainer_state.json
ADDED
@@ -0,0 +1,4291 @@
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|
|
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|
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