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finetuned llama3.2-3b on lima with train set
Browse files- .gitattributes +1 -0
- README.md +61 -0
- adapter_config.json +3 -0
- adapter_model.safetensors +3 -0
- all_results.json +3 -0
- checkpoint-270/README.md +202 -0
- checkpoint-270/adapter_config.json +3 -0
- checkpoint-270/adapter_model.safetensors +3 -0
- checkpoint-270/optimizer.pt +3 -0
- checkpoint-270/rng_state.pth +3 -0
- checkpoint-270/scheduler.pt +3 -0
- checkpoint-270/special_tokens_map.json +3 -0
- checkpoint-270/tokenizer.json +3 -0
- checkpoint-270/tokenizer_config.json +3 -0
- checkpoint-270/trainer_state.json +3 -0
- checkpoint-270/training_args.bin +3 -0
- eval_results.json +3 -0
- special_tokens_map.json +3 -0
- tokenizer.json +3 -0
- tokenizer_config.json +3 -0
- train_results.json +3 -0
- trainer_log.jsonl +28 -0
- trainer_state.json +3 -0
- training_args.bin +3 -0
- training_loss.png +0 -0
.gitattributes
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README.md
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---
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library_name: peft
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license: other
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base_model: meta-llama/Llama-3.2-3B-Instruct
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tags:
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- llama-factory
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- lora
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- generated_from_trainer
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model-index:
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- name: lima
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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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# lima
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This model is a fine-tuned version of [meta-llama/Llama-3.2-3B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct) on the lima_train dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.1396
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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: 0.0001
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- train_batch_size: 1
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- eval_batch_size: 1
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- seed: 42
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- gradient_accumulation_steps: 8
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- total_train_batch_size: 8
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 3.0
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### Training results
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### Framework versions
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- PEFT 0.12.0
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- Transformers 4.46.1
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- Pytorch 2.5.1+cu124
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- Datasets 3.1.0
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- Tokenizers 0.20.3
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adapter_config.json
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version https://git-lfs.github.com/spec/v1
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oid sha256:bcae1cdc0ab630ade29b36af71ec6bdc306c14730e424c3ff59fcae008aecb64
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size 733
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adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:57ac7ed54c9463801afe6e720e90fe461919b4e63070da4434b35bee9499c676
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size 48679352
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all_results.json
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version https://git-lfs.github.com/spec/v1
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oid sha256:d6b7714e0ba53b9b2875f366c76517b7c0ff1ce33c78b98e97f34bf1a5495f08
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size 346
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checkpoint-270/README.md
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---
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base_model: meta-llama/Llama-3.2-3B-Instruct
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library_name: peft
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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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- **Funded by [optional]:** [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 Dataset 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 Dataset 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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### Framework versions
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- PEFT 0.12.0
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checkpoint-270/adapter_config.json
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version https://git-lfs.github.com/spec/v1
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oid sha256:bcae1cdc0ab630ade29b36af71ec6bdc306c14730e424c3ff59fcae008aecb64
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size 733
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checkpoint-270/adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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size 48679352
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checkpoint-270/optimizer.pt
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version https://git-lfs.github.com/spec/v1
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size 97585002
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checkpoint-270/rng_state.pth
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version https://git-lfs.github.com/spec/v1
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checkpoint-270/scheduler.pt
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version https://git-lfs.github.com/spec/v1
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size 1064
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checkpoint-270/special_tokens_map.json
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version https://git-lfs.github.com/spec/v1
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size 650
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checkpoint-270/tokenizer.json
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version https://git-lfs.github.com/spec/v1
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tokenizer.json
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tokenizer_config.json
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train_results.json
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trainer_log.jsonl
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trainer_state.json
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training_args.bin
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training_loss.png
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