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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: mistralai/Mistral-7B-Instruct-v0.2 |
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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: Na_M2_1000steps_1e6rate_SFT |
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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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# Na_M2_1000steps_1e6rate_SFT |
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This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1550 |
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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: 1e-06 |
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- train_batch_size: 2 |
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- eval_batch_size: 1 |
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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: cosine |
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- lr_scheduler_warmup_steps: 100 |
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- training_steps: 1000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 0.349 | 0.2667 | 50 | 0.3425 | |
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| 0.2797 | 0.5333 | 100 | 0.2671 | |
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| 0.1882 | 0.8 | 150 | 0.1831 | |
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| 0.1593 | 1.0667 | 200 | 0.1748 | |
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| 0.1609 | 1.3333 | 250 | 0.1586 | |
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| 0.1544 | 1.6 | 300 | 0.1575 | |
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| 0.1558 | 1.8667 | 350 | 0.1564 | |
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| 0.1524 | 2.1333 | 400 | 0.1574 | |
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| 0.1527 | 2.4 | 450 | 0.1568 | |
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| 0.1564 | 2.6667 | 500 | 0.1554 | |
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| 0.1523 | 2.9333 | 550 | 0.1563 | |
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| 0.1519 | 3.2 | 600 | 0.1558 | |
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| 0.1532 | 3.4667 | 650 | 0.1555 | |
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| 0.1508 | 3.7333 | 700 | 0.1549 | |
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| 0.1518 | 4.0 | 750 | 0.1550 | |
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| 0.1507 | 4.2667 | 800 | 0.1551 | |
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| 0.1501 | 4.5333 | 850 | 0.1550 | |
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| 0.1477 | 4.8 | 900 | 0.1549 | |
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| 0.1464 | 5.0667 | 950 | 0.1550 | |
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| 0.1488 | 5.3333 | 1000 | 0.1550 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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