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--- |
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license: mit |
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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: microsoft/Phi-3-medium-128k-instruct |
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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 [microsoft/Phi-3-medium-128k-instruct](https://huggingface.co/microsoft/Phi-3-medium-128k-instruct) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3259 |
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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: 5e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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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: linear |
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- num_epochs: 3 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 2.102 | 0.1065 | 100 | 2.1266 | |
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| 2.0156 | 0.2130 | 200 | 1.9941 | |
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| 1.8151 | 0.3195 | 300 | 1.8149 | |
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| 1.6951 | 0.4260 | 400 | 1.5771 | |
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| 1.2789 | 0.5325 | 500 | 1.3936 | |
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| 1.0007 | 0.6390 | 600 | 1.1524 | |
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| 0.7882 | 0.7455 | 700 | 0.9936 | |
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| 0.9486 | 0.8520 | 800 | 0.8539 | |
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| 0.7381 | 0.9585 | 900 | 0.7410 | |
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| 0.6254 | 1.0650 | 1000 | 0.6283 | |
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| 0.4915 | 1.1715 | 1100 | 0.5834 | |
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| 0.3432 | 1.2780 | 1200 | 0.5034 | |
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| 0.349 | 1.3845 | 1300 | 0.4476 | |
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| 0.4378 | 1.4909 | 1400 | 0.4160 | |
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| 0.4522 | 1.5974 | 1500 | 0.4061 | |
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| 0.3183 | 1.7039 | 1600 | 0.3795 | |
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| 0.3184 | 1.8104 | 1700 | 0.3707 | |
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| 0.267 | 1.9169 | 1800 | 0.3601 | |
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| 0.2966 | 2.0234 | 1900 | 0.3538 | |
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| 0.2697 | 2.1299 | 2000 | 0.3492 | |
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| 0.3662 | 2.2364 | 2100 | 0.3424 | |
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| 0.3135 | 2.3429 | 2200 | 0.3407 | |
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| 0.3339 | 2.4494 | 2300 | 0.3366 | |
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| 0.1828 | 2.5559 | 2400 | 0.3340 | |
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| 0.2824 | 2.6624 | 2500 | 0.3306 | |
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| 0.3204 | 2.7689 | 2600 | 0.3289 | |
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| 0.3062 | 2.8754 | 2700 | 0.3263 | |
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| 0.313 | 2.9819 | 2800 | 0.3259 | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.41.2 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
