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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: NXAIR_M_mistral-7B |
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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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# NXAIR_M_mistral-7B |
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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: 0.6929 |
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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: 0.00025 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: constant |
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- lr_scheduler_warmup_ratio: 0.03 |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 1.1435 | 0.0702 | 100 | 1.1971 | |
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| 1.0993 | 0.1404 | 200 | 1.0390 | |
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| 1.0643 | 0.2107 | 300 | 0.9309 | |
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| 0.956 | 0.2809 | 400 | 0.9125 | |
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| 0.9906 | 0.3511 | 500 | 0.8591 | |
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| 0.9083 | 0.4213 | 600 | 0.8703 | |
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| 0.8951 | 0.4916 | 700 | 0.8179 | |
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| 0.8352 | 0.5618 | 800 | 0.7852 | |
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| 0.8472 | 0.6320 | 900 | 0.7772 | |
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| 0.8733 | 0.7022 | 1000 | 0.7447 | |
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| 0.7958 | 0.7725 | 1100 | 0.7082 | |
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| 0.8726 | 0.8427 | 1200 | 0.7125 | |
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| 0.804 | 0.9129 | 1300 | 0.6909 | |
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| 0.8467 | 0.9831 | 1400 | 0.7287 | |
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| 0.4705 | 1.0534 | 1500 | 0.6921 | |
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| 0.4864 | 1.1236 | 1600 | 0.6648 | |
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| 0.4535 | 1.1938 | 1700 | 0.6765 | |
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| 0.4542 | 1.2640 | 1800 | 0.6620 | |
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| 0.4789 | 1.3343 | 1900 | 0.6584 | |
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| 0.5154 | 1.4045 | 2000 | 0.6492 | |
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| 0.459 | 1.4747 | 2100 | 0.6647 | |
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| 0.5168 | 1.5449 | 2200 | 0.6484 | |
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| 0.483 | 1.6152 | 2300 | 0.6795 | |
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| 0.4768 | 1.6854 | 2400 | 0.6730 | |
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| 0.4821 | 1.7556 | 2500 | 0.6404 | |
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| 0.4929 | 1.8258 | 2600 | 0.6409 | |
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| 0.5438 | 1.8961 | 2700 | 0.6551 | |
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| 0.4598 | 1.9663 | 2800 | 0.6740 | |
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| 0.4902 | 2.0365 | 2900 | 0.7287 | |
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| 0.5058 | 2.1067 | 3000 | 0.7142 | |
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| 0.4615 | 2.1770 | 3100 | 0.6929 | |
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### Framework versions |
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- PEFT 0.10.0 |
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- Transformers 4.40.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
