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--- |
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license: mit |
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base_model: microsoft/phi-2 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: V0507HMA15HV2 |
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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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# V0507HMA15HV2 |
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This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: -95.0498 |
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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: 100 |
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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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| -8.6532 | 0.09 | 10 | -10.3327 | |
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| -11.8451 | 0.18 | 20 | -14.2014 | |
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| -17.3537 | 0.27 | 30 | -22.7794 | |
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| -28.8388 | 0.36 | 40 | -38.5512 | |
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| -47.1885 | 0.45 | 50 | -59.6364 | |
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| -67.2573 | 0.54 | 60 | -76.6591 | |
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| -81.223 | 0.63 | 70 | -86.3414 | |
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| -87.9651 | 0.73 | 80 | -90.0475 | |
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| -91.3192 | 0.82 | 90 | -92.4350 | |
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| -92.7456 | 0.91 | 100 | -93.1825 | |
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| -93.4032 | 1.0 | 110 | -93.7378 | |
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| -93.8855 | 1.09 | 120 | -93.9331 | |
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| -94.0075 | 1.18 | 130 | -93.9987 | |
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| -94.001 | 1.27 | 140 | -94.3115 | |
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| -94.3566 | 1.36 | 150 | -94.4505 | |
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| -94.3346 | 1.45 | 160 | -94.2625 | |
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| -94.5793 | 1.54 | 170 | -94.3309 | |
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| -93.2701 | 1.63 | 180 | -93.4388 | |
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| -94.2829 | 1.72 | 190 | -93.8681 | |
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| -94.6778 | 1.81 | 200 | -94.7489 | |
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| -94.5762 | 1.9 | 210 | -94.7745 | |
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| -94.8427 | 1.99 | 220 | -94.8903 | |
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| -94.8653 | 2.08 | 230 | -94.8499 | |
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| -94.9237 | 2.18 | 240 | -94.9720 | |
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| -95.0027 | 2.27 | 250 | -94.9841 | |
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| -94.9404 | 2.36 | 260 | -94.8479 | |
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| -94.9594 | 2.45 | 270 | -95.0076 | |
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| -95.0772 | 2.54 | 280 | -95.0798 | |
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| -95.0775 | 2.63 | 290 | -95.0480 | |
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| -95.0528 | 2.72 | 300 | -95.0415 | |
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| -95.0652 | 2.81 | 310 | -95.0442 | |
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| -95.0738 | 2.9 | 320 | -95.0494 | |
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| -95.0694 | 2.99 | 330 | -95.0498 | |
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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 2.18.0 |
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- Tokenizers 0.14.1 |
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