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--- |
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license: mit |
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base_model: microsoft/Phi-3-mini-4k-instruct |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: Phi0503HMA1 |
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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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# Phi0503HMA1 |
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This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1635 |
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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: 0.0003 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine_with_restarts |
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- lr_scheduler_warmup_steps: 80 |
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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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| 4.5767 | 0.09 | 10 | 1.3277 | |
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| 0.528 | 0.18 | 20 | 0.2431 | |
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| 0.272 | 0.27 | 30 | 0.2412 | |
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| 0.4937 | 0.36 | 40 | 1.1132 | |
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| 0.3726 | 0.45 | 50 | 0.2147 | |
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| 0.2214 | 0.54 | 60 | 0.2026 | |
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| 0.3024 | 0.63 | 70 | 0.1963 | |
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| 0.2358 | 0.73 | 80 | 0.2236 | |
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| 0.1673 | 0.82 | 90 | 0.1289 | |
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| 0.1417 | 0.91 | 100 | 0.3550 | |
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| 0.6614 | 1.0 | 110 | 0.2344 | |
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| 0.2316 | 1.09 | 120 | 0.1982 | |
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| 0.3203 | 1.18 | 130 | 0.1760 | |
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| 0.2092 | 1.27 | 140 | 0.1681 | |
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| 0.1788 | 1.36 | 150 | 0.1693 | |
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| 0.8967 | 1.45 | 160 | 1.4252 | |
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| 0.7768 | 1.54 | 170 | 0.1814 | |
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| 0.1745 | 1.63 | 180 | 0.1690 | |
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| 0.1651 | 1.72 | 190 | 0.1664 | |
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| 0.1648 | 1.81 | 200 | 0.1655 | |
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| 0.1678 | 1.9 | 210 | 0.1649 | |
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| 0.164 | 1.99 | 220 | 0.1642 | |
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| 0.1646 | 2.08 | 230 | 0.1630 | |
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| 0.1609 | 2.18 | 240 | 0.1630 | |
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| 0.1601 | 2.27 | 250 | 0.1636 | |
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| 0.1634 | 2.36 | 260 | 0.1642 | |
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| 0.1616 | 2.45 | 270 | 0.1640 | |
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| 0.1619 | 2.54 | 280 | 0.1642 | |
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| 0.1624 | 2.63 | 290 | 0.1642 | |
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| 0.1634 | 2.72 | 300 | 0.1638 | |
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| 0.1634 | 2.81 | 310 | 0.1635 | |
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| 0.1619 | 2.9 | 320 | 0.1635 | |
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| 0.1665 | 2.99 | 330 | 0.1635 | |
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### Framework versions |
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- Transformers 4.36.0.dev0 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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