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--- |
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base_model: mistralai/Mistral-7B-Instruct-v0.3 |
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library_name: peft |
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license: apache-2.0 |
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tags: |
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- trl |
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- sft |
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- generated_from_trainer |
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model-index: |
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- name: Mistral-7B_task-2_120-samples_config-2_full_auto |
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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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# Mistral-7B_task-2_120-samples_config-2_full_auto |
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This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co./mistralai/Mistral-7B-Instruct-v0.3) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9351 |
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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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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 16 |
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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_ratio: 0.1 |
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- num_epochs: 50 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-------:|:----:|:---------------:| |
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| 1.1522 | 0.9091 | 5 | 1.0969 | |
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| 1.0455 | 2.0 | 11 | 0.9818 | |
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| 0.9291 | 2.9091 | 16 | 0.9178 | |
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| 0.8133 | 4.0 | 22 | 0.8174 | |
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| 0.754 | 4.9091 | 27 | 0.7907 | |
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| 0.7232 | 6.0 | 33 | 0.7768 | |
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| 0.7137 | 6.9091 | 38 | 0.7700 | |
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| 0.6783 | 8.0 | 44 | 0.7681 | |
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| 0.6309 | 8.9091 | 49 | 0.7697 | |
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| 0.6237 | 10.0 | 55 | 0.7780 | |
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| 0.5633 | 10.9091 | 60 | 0.7931 | |
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| 0.4943 | 12.0 | 66 | 0.8165 | |
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| 0.4499 | 12.9091 | 71 | 0.8476 | |
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| 0.4037 | 14.0 | 77 | 0.9135 | |
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| 0.3067 | 14.9091 | 82 | 0.9351 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.44.0 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
