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--- |
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library_name: transformers |
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license: mit |
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base_model: emilyalsentzer/Bio_ClinicalBERT |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: BioMedRoBERTa-finetuned-ner-pablo-just-classifier |
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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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# BioMedRoBERTa-finetuned-ner-pablo-just-classifier |
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This model is a fine-tuned version of [emilyalsentzer/Bio_ClinicalBERT](https://huggingface.co/emilyalsentzer/Bio_ClinicalBERT) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1150 |
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- Precision: 0.6869 |
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- Recall: 0.7076 |
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- F1: 0.6971 |
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- Accuracy: 0.9677 |
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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: 0.1 |
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- train_batch_size: 128 |
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- eval_batch_size: 128 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 512 |
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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_ratio: 0.05 |
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- num_epochs: 10 |
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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 | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| No log | 0.9655 | 14 | 0.3729 | 0.4205 | 0.6119 | 0.4985 | 0.9430 | |
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| No log | 2.0 | 29 | 0.2544 | 0.5272 | 0.6683 | 0.5894 | 0.9574 | |
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| No log | 2.9655 | 43 | 0.2117 | 0.5702 | 0.6884 | 0.6238 | 0.9604 | |
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| No log | 4.0 | 58 | 0.1747 | 0.5934 | 0.7001 | 0.6424 | 0.9628 | |
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| No log | 4.9655 | 72 | 0.1420 | 0.6280 | 0.6827 | 0.6542 | 0.9642 | |
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| No log | 6.0 | 87 | 0.1287 | 0.6639 | 0.7033 | 0.6830 | 0.9667 | |
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| No log | 6.9655 | 101 | 0.1309 | 0.6471 | 0.7009 | 0.6729 | 0.9654 | |
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| No log | 8.0 | 116 | 0.1260 | 0.6349 | 0.7199 | 0.6748 | 0.9652 | |
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| No log | 8.9655 | 130 | 0.1159 | 0.6621 | 0.7118 | 0.6860 | 0.9670 | |
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| No log | 9.6552 | 140 | 0.1150 | 0.6869 | 0.7076 | 0.6971 | 0.9677 | |
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### Framework versions |
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- Transformers 4.44.1 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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