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--- |
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library_name: transformers |
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base_model: yikuan8/Clinical-Longformer |
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tags: |
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- generated_from_trainer |
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metrics: |
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- f1 |
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model-index: |
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- name: finetuned_ClinicalLongformer_newData_undersampling |
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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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# finetuned_ClinicalLongformer_newData_undersampling |
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This model is a fine-tuned version of [yikuan8/Clinical-Longformer](https://huggingface.co/yikuan8/Clinical-Longformer) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5173 |
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- F1: 0.7647 |
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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: 1e-05 |
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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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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 0.6886 | 1.0 | 12 | 0.7002 | 0.56 | |
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| 0.6558 | 2.0 | 24 | 0.6807 | 0.6087 | |
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| 0.6087 | 3.0 | 36 | 0.5738 | 0.7568 | |
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| 0.5527 | 4.0 | 48 | 0.5173 | 0.7647 | |
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| 0.3949 | 5.0 | 60 | 0.5088 | 0.6897 | |
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| 0.3269 | 6.0 | 72 | 0.5050 | 0.7222 | |
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| 0.3196 | 7.0 | 84 | 0.5267 | 0.6897 | |
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| 0.2235 | 8.0 | 96 | 0.5024 | 0.7333 | |
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| 0.1633 | 9.0 | 108 | 0.4877 | 0.7143 | |
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| 0.136 | 10.0 | 120 | 0.5723 | 0.6667 | |
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| 0.1101 | 11.0 | 132 | 0.6704 | 0.6429 | |
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| 0.0673 | 12.0 | 144 | 0.7958 | 0.6897 | |
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| 0.0795 | 13.0 | 156 | 0.8270 | 0.6154 | |
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| 0.0716 | 14.0 | 168 | 0.8288 | 0.5926 | |
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| 0.0297 | 15.0 | 180 | 0.9462 | 0.6154 | |
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| 0.0236 | 16.0 | 192 | 1.0562 | 0.56 | |
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| 0.2009 | 17.0 | 204 | 1.0884 | 0.6429 | |
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| 0.0298 | 18.0 | 216 | 1.1095 | 0.6429 | |
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| 0.0134 | 19.0 | 228 | 1.1237 | 0.5926 | |
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| 0.0147 | 20.0 | 240 | 1.1291 | 0.5926 | |
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### Framework versions |
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- Transformers 4.48.0 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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