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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: PHI30515HMA2H |
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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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# PHI30515HMA2H |
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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: 0.0706 |
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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: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 32 |
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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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| 7.1779 | 0.09 | 10 | 2.1285 | |
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| 1.3773 | 0.18 | 20 | 0.3216 | |
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| 0.3479 | 0.27 | 30 | 0.2281 | |
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| 0.9413 | 0.36 | 40 | 0.3169 | |
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| 0.2771 | 0.45 | 50 | 0.1485 | |
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| 0.332 | 0.54 | 60 | 0.1472 | |
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| 0.2391 | 0.63 | 70 | 0.1359 | |
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| 0.1792 | 0.73 | 80 | 0.1238 | |
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| 0.1223 | 0.82 | 90 | 0.1178 | |
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| 0.1279 | 0.91 | 100 | 0.0860 | |
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| 0.109 | 1.0 | 110 | 0.0776 | |
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| 0.0986 | 1.09 | 120 | 0.0769 | |
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| 0.0989 | 1.18 | 130 | 0.0739 | |
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| 0.117 | 1.27 | 140 | 0.0712 | |
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| 0.1134 | 1.36 | 150 | 0.0686 | |
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| 0.0768 | 1.45 | 160 | 0.0661 | |
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| 0.0932 | 1.54 | 170 | 0.1176 | |
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| 0.0865 | 1.63 | 180 | 0.0759 | |
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| 0.0974 | 1.72 | 190 | 0.0680 | |
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| 0.0831 | 1.81 | 200 | 0.0715 | |
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| 0.0732 | 1.9 | 210 | 0.1637 | |
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| 0.0756 | 1.99 | 220 | 0.0676 | |
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| 0.0457 | 2.08 | 230 | 0.0696 | |
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| 0.0551 | 2.18 | 240 | 0.0779 | |
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| 0.0391 | 2.27 | 250 | 0.0772 | |
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| 0.0401 | 2.36 | 260 | 0.0749 | |
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| 0.0448 | 2.45 | 270 | 0.0707 | |
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| 0.0422 | 2.54 | 280 | 0.0731 | |
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| 0.037 | 2.63 | 290 | 0.0732 | |
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| 0.039 | 2.72 | 300 | 0.0727 | |
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| 0.0465 | 2.81 | 310 | 0.0718 | |
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| 0.051 | 2.9 | 320 | 0.0707 | |
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| 0.0416 | 2.99 | 330 | 0.0706 | |
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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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