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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: Phi0511B2 |
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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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# Phi0511B2 |
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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: 0.0718 |
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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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| 5.4836 | 0.09 | 10 | 5.4324 | |
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| 5.4542 | 0.18 | 20 | 5.2447 | |
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| 4.9491 | 0.27 | 30 | 4.1820 | |
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| 3.3816 | 0.36 | 40 | 2.1650 | |
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| 1.3373 | 0.45 | 50 | 0.5823 | |
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| 0.4096 | 0.54 | 60 | 0.1966 | |
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| 0.1569 | 0.63 | 70 | 0.1428 | |
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| 0.1378 | 0.73 | 80 | 0.1266 | |
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| 0.1135 | 0.82 | 90 | 0.1250 | |
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| 0.127 | 0.91 | 100 | 0.1191 | |
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| 0.1078 | 1.0 | 110 | 0.1075 | |
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| 0.0958 | 1.09 | 120 | 0.0948 | |
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| 0.0877 | 1.18 | 130 | 0.0946 | |
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| 0.0995 | 1.27 | 140 | 0.0841 | |
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| 0.0822 | 1.36 | 150 | 0.1001 | |
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| 0.0901 | 1.45 | 160 | 0.0814 | |
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| 0.0754 | 1.54 | 170 | 0.0833 | |
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| 0.0806 | 1.63 | 180 | 0.1000 | |
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| 0.0763 | 1.72 | 190 | 0.0800 | |
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| 0.0787 | 1.81 | 200 | 0.0787 | |
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| 0.0637 | 1.9 | 210 | 0.0753 | |
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| 0.0657 | 1.99 | 220 | 0.0799 | |
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| 0.0605 | 2.08 | 230 | 0.0777 | |
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| 0.0625 | 2.18 | 240 | 0.0740 | |
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| 0.0544 | 2.27 | 250 | 0.0743 | |
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| 0.0572 | 2.36 | 260 | 0.0736 | |
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| 0.0593 | 2.45 | 270 | 0.0739 | |
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| 0.0575 | 2.54 | 280 | 0.0729 | |
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| 0.0584 | 2.63 | 290 | 0.0737 | |
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| 0.057 | 2.72 | 300 | 0.0728 | |
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| 0.0622 | 2.81 | 310 | 0.0720 | |
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| 0.0566 | 2.9 | 320 | 0.0718 | |
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| 0.0594 | 2.99 | 330 | 0.0718 | |
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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 0.14.0 |
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