Commit
•
c71bb36
1
Parent(s):
e69b2ec
Training in progress, epoch 3, checkpoint
Browse files- checkpoint-5172/README.md +219 -0
- checkpoint-5172/adapter_config.json +31 -0
- checkpoint-5172/adapter_model.bin +3 -0
- checkpoint-5172/optimizer.pt +3 -0
- checkpoint-5172/rng_state.pth +3 -0
- checkpoint-5172/scheduler.pt +3 -0
- checkpoint-5172/trainer_state.json +0 -0
- checkpoint-5172/training_args.bin +3 -0
checkpoint-5172/README.md
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---
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library_name: peft
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base_model: chargoddard/Yi-34B-Llama
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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
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## Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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## Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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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).
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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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- **Cloud Provider:** [More Information Needed]
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- **Compute Region:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
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## Technical Specifications [optional]
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### Model Architecture and Objective
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[More Information Needed]
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### Compute Infrastructure
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[More Information Needed]
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#### Hardware
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[More Information Needed]
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#### Software
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[More Information Needed]
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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[More Information Needed]
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**APA:**
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[More Information Needed]
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## Glossary [optional]
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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[More Information Needed]
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## More Information [optional]
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[More Information Needed]
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## Model Card Authors [optional]
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[More Information Needed]
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## Model Card Contact
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[More Information Needed]
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## Training procedure
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The following `bitsandbytes` quantization config was used during training:
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- quant_method: bitsandbytes
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- load_in_8bit: False
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- load_in_4bit: True
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- llm_int8_threshold: 6.0
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- llm_int8_skip_modules: None
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- llm_int8_enable_fp32_cpu_offload: False
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- llm_int8_has_fp16_weight: False
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- bnb_4bit_quant_type: nf4
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- bnb_4bit_use_double_quant: True
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- bnb_4bit_compute_dtype: bfloat16
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### Framework versions
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- PEFT 0.7.0.dev0
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checkpoint-5172/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": "chargoddard/Yi-34B-Llama",
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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": 256,
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"lora_dropout": 0.05,
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"modules_to_save": [
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"embed_tokens",
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"lm_head"
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],
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"peft_type": "LORA",
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"r": 128,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"gate_proj",
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"k_proj",
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"q_proj",
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"up_proj",
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"v_proj",
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"o_proj",
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"down_proj"
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],
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"task_type": "CAUSAL_LM"
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}
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checkpoint-5172/adapter_model.bin
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:d944bee217e87b6c2c2c8c229ced17d950d97fa9e6572fea94102e0a17e7f4c8
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size 5767472341
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checkpoint-5172/optimizer.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:1934ce81a5d83b7dd72beb847dedd0a874e17efde9d45d952b06e8208ee24cea
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size 3809522119
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checkpoint-5172/rng_state.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:4564cea6100375a86e5bc86d6dbf978e2397dca5bbe131191c4d6d6a03dd90e0
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size 14575
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checkpoint-5172/scheduler.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:62876236d97d82caa6ef7d08dd52701b1ac8fd640be45af5fbc205e2c9e7c82d
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size 627
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checkpoint-5172/trainer_state.json
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checkpoint-5172/training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:8d032ac0cf8f5ada42f270785b282aae040ccfc1ffd009f12b06beb7f96302a7
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size 4539
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