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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: V0507HMA15HB2 |
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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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# V0507HMA15HB2 |
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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: -81.6054 |
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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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| -10.1232 | 0.09 | 10 | -11.7425 | |
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| -13.0448 | 0.18 | 20 | -15.0037 | |
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| -17.5347 | 0.27 | 30 | -21.6644 | |
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| -25.551 | 0.36 | 40 | -31.2337 | |
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| -35.3456 | 0.45 | 50 | -41.1929 | |
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| -44.7681 | 0.54 | 60 | -50.2314 | |
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| -53.1455 | 0.63 | 70 | -57.6267 | |
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| -59.6872 | 0.73 | 80 | -63.3874 | |
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| -65.1855 | 0.82 | 90 | -67.4235 | |
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| -67.6972 | 0.91 | 100 | -68.9758 | |
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| -70.4407 | 1.0 | 110 | -72.7099 | |
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| -73.0595 | 1.09 | 120 | -72.9839 | |
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| -72.4114 | 1.18 | 130 | -73.4895 | |
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| -73.3489 | 1.27 | 140 | -73.0341 | |
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| -68.9142 | 1.36 | 150 | -71.6919 | |
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| -75.8434 | 1.45 | 160 | -76.9335 | |
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| -77.7082 | 1.54 | 170 | -79.3035 | |
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| -79.5405 | 1.63 | 180 | -78.0217 | |
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| -73.5315 | 1.72 | 190 | -72.0316 | |
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| -72.5674 | 1.81 | 200 | -74.5039 | |
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| -76.8928 | 1.9 | 210 | -77.8919 | |
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| -78.6004 | 1.99 | 220 | -79.7306 | |
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| -79.779 | 2.08 | 230 | -78.9037 | |
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| -78.5156 | 2.18 | 240 | -78.2094 | |
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| -77.3853 | 2.27 | 250 | -74.1239 | |
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| -77.7728 | 2.36 | 260 | -79.7795 | |
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| -80.4204 | 2.45 | 270 | -81.1776 | |
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| -81.1502 | 2.54 | 280 | -81.5114 | |
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| -81.4538 | 2.63 | 290 | -81.3391 | |
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| -81.3301 | 2.72 | 300 | -81.3797 | |
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| -81.3074 | 2.81 | 310 | -81.5299 | |
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| -81.527 | 2.9 | 320 | -81.5893 | |
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| -81.5978 | 2.99 | 330 | -81.6054 | |
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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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