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--- |
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license: apache-2.0 |
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base_model: google/t5-efficient-small |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: medication-single-t5 |
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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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# medication-single-t5 |
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This model is a fine-tuned version of [google/t5-efficient-small](https://huggingface.co/google/t5-efficient-small) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0134 |
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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: 0.004 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.03 |
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- num_epochs: 2 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 0.5257 | 0.08 | 100 | 0.2084 | |
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| 0.1412 | 0.16 | 200 | 0.0880 | |
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| 0.0902 | 0.23 | 300 | 0.0543 | |
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| 0.0791 | 0.31 | 400 | 0.0456 | |
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| 0.072 | 0.39 | 500 | 0.0392 | |
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| 0.0567 | 0.47 | 600 | 0.0349 | |
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| 0.0507 | 0.55 | 700 | 0.0312 | |
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| 0.0493 | 0.63 | 800 | 0.0285 | |
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| 0.041 | 0.7 | 900 | 0.0246 | |
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| 0.0423 | 0.78 | 1000 | 0.0255 | |
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| 0.0382 | 0.86 | 1100 | 0.0247 | |
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| 0.0375 | 0.94 | 1200 | 0.0217 | |
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| 0.0298 | 1.02 | 1300 | 0.0211 | |
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| 0.0327 | 1.09 | 1400 | 0.0198 | |
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| 0.0272 | 1.17 | 1500 | 0.0195 | |
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| 0.0301 | 1.25 | 1600 | 0.0183 | |
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| 0.0259 | 1.33 | 1700 | 0.0179 | |
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| 0.0273 | 1.41 | 1800 | 0.0164 | |
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| 0.0244 | 1.49 | 1900 | 0.0163 | |
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| 0.0222 | 1.56 | 2000 | 0.0161 | |
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| 0.0214 | 1.64 | 2100 | 0.0158 | |
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| 0.0199 | 1.72 | 2200 | 0.0146 | |
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| 0.0202 | 1.8 | 2300 | 0.0141 | |
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| 0.0214 | 1.88 | 2400 | 0.0135 | |
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| 0.018 | 1.95 | 2500 | 0.0134 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.7 |
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- Tokenizers 0.14.1 |
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