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--- |
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base_model: mistralai/Mistral-7B-v0.1 |
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library_name: peft |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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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 the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4476 |
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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: 0.001 |
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- train_batch_size: 2 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 4 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 17 |
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- training_steps: 1792 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 2.8156 | 0.1115 | 50 | 1.7682 | |
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| 1.6754 | 0.2230 | 100 | 1.6347 | |
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| 1.5257 | 0.3344 | 150 | 1.5543 | |
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| 1.5435 | 0.4459 | 200 | 1.5301 | |
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| 1.613 | 0.5574 | 250 | 1.5579 | |
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| 1.6178 | 0.6689 | 300 | 1.6006 | |
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| 1.675 | 0.7804 | 350 | 1.5209 | |
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| 1.5046 | 0.8919 | 400 | 1.5203 | |
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| 1.5977 | 1.0033 | 450 | 1.5253 | |
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| 1.5303 | 1.1148 | 500 | 1.4984 | |
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| 1.4748 | 1.2263 | 550 | 1.5073 | |
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| 1.4955 | 1.3378 | 600 | 1.4998 | |
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| 1.5737 | 1.4493 | 650 | 1.5405 | |
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| 1.5662 | 1.5608 | 700 | 1.5147 | |
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| 1.417 | 1.6722 | 750 | 1.5047 | |
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| 1.5732 | 1.7837 | 800 | 1.4768 | |
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| 1.5077 | 1.8952 | 850 | 1.4948 | |
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| 1.5634 | 2.0067 | 900 | 1.4768 | |
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| 1.5219 | 2.1182 | 950 | 1.4752 | |
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| 1.4073 | 2.2297 | 1000 | 1.4776 | |
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| 1.4915 | 2.3411 | 1050 | 1.4799 | |
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| 1.4585 | 2.4526 | 1100 | 1.4868 | |
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| 1.4979 | 2.5641 | 1150 | 1.4703 | |
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| 1.4755 | 2.6756 | 1200 | 1.4617 | |
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| 1.4167 | 2.7871 | 1250 | 1.4576 | |
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| 1.5095 | 2.8986 | 1300 | 1.4651 | |
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| 1.477 | 3.0100 | 1350 | 1.4526 | |
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| 1.4495 | 3.1215 | 1400 | 1.4660 | |
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| 1.5609 | 3.2330 | 1450 | 1.4547 | |
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| 1.4319 | 3.3445 | 1500 | 1.4478 | |
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| 1.3469 | 3.4560 | 1550 | 1.4597 | |
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| 1.4454 | 3.5674 | 1600 | 1.4478 | |
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| 1.4071 | 3.6789 | 1650 | 1.4506 | |
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| 1.3686 | 3.7904 | 1700 | 1.4485 | |
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| 1.4958 | 3.9019 | 1750 | 1.4476 | |
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### Framework versions |
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- PEFT 0.13.0 |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.1 |
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- Tokenizers 0.19.1 |
