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--- |
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license: apache-2.0 |
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library_name: peft |
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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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base_model: mistralai/Mistral-7B-v0.1 |
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model-index: |
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- name: results |
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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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# results |
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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 an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9724 |
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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: 0.0002 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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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: 0.03 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 1.0248 | 0.03 | 50 | 1.0145 | |
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| 1.0168 | 0.06 | 100 | 1.0078 | |
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| 1.008 | 0.09 | 150 | 1.0058 | |
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| 1.0082 | 0.12 | 200 | 1.0030 | |
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| 0.9846 | 0.14 | 250 | 1.0005 | |
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| 0.9807 | 0.17 | 300 | 0.9998 | |
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| 0.9968 | 0.2 | 350 | 0.9992 | |
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| 0.9834 | 0.23 | 400 | 0.9967 | |
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| 1.0267 | 0.26 | 450 | 0.9953 | |
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| 1.0119 | 0.29 | 500 | 0.9937 | |
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| 0.9759 | 0.32 | 550 | 0.9939 | |
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| 0.9978 | 0.35 | 600 | 0.9921 | |
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| 1.0145 | 0.38 | 650 | 0.9901 | |
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| 1.0064 | 0.4 | 700 | 0.9897 | |
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| 0.9949 | 0.43 | 750 | 0.9890 | |
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| 0.9936 | 0.46 | 800 | 0.9865 | |
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| 0.9944 | 0.49 | 850 | 0.9852 | |
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| 0.9819 | 0.52 | 900 | 0.9845 | |
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| 0.9991 | 0.55 | 950 | 0.9826 | |
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| 0.9874 | 0.58 | 1000 | 0.9812 | |
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| 0.981 | 0.61 | 1050 | 0.9798 | |
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| 0.9807 | 0.64 | 1100 | 0.9789 | |
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| 0.9639 | 0.67 | 1150 | 0.9776 | |
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| 0.9645 | 0.69 | 1200 | 0.9767 | |
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| 0.9788 | 0.72 | 1250 | 0.9758 | |
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| 0.9823 | 0.75 | 1300 | 0.9751 | |
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| 0.9906 | 0.78 | 1350 | 0.9745 | |
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| 0.9536 | 0.81 | 1400 | 0.9738 | |
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| 0.9635 | 0.84 | 1450 | 0.9732 | |
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| 0.9754 | 0.87 | 1500 | 0.9729 | |
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| 0.9785 | 0.9 | 1550 | 0.9727 | |
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| 0.9828 | 0.93 | 1600 | 0.9725 | |
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| 0.9951 | 0.95 | 1650 | 0.9724 | |
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| 0.983 | 0.98 | 1700 | 0.9724 | |
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### Framework versions |
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- PEFT 0.9.0 |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
