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--- |
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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: NLP-HIBA_DisTEMIST_fine_tuned_ClinicalBERT-pretrained-model |
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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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# NLP-HIBA_DisTEMIST_fine_tuned_ClinicalBERT-pretrained-model |
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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: 0.2557 |
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- Precision: 0.4943 |
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- Recall: 0.5046 |
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- F1: 0.4994 |
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- Accuracy: 0.9407 |
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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: 5e-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: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 12 |
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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 | 1.0 | 71 | 0.2423 | 0.1951 | 0.1433 | 0.1653 | 0.9109 | |
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| No log | 2.0 | 142 | 0.2177 | 0.2905 | 0.3474 | 0.3164 | 0.9138 | |
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| No log | 3.0 | 213 | 0.1822 | 0.3912 | 0.3701 | 0.3804 | 0.9325 | |
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| No log | 4.0 | 284 | 0.1845 | 0.3839 | 0.4367 | 0.4086 | 0.9298 | |
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| No log | 5.0 | 355 | 0.2033 | 0.4533 | 0.4271 | 0.4398 | 0.9367 | |
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| No log | 6.0 | 426 | 0.2005 | 0.4535 | 0.4736 | 0.4633 | 0.9365 | |
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| No log | 7.0 | 497 | 0.2297 | 0.4352 | 0.5155 | 0.4720 | 0.9321 | |
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| 0.1436 | 8.0 | 568 | 0.2236 | 0.4854 | 0.4656 | 0.4753 | 0.9395 | |
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| 0.1436 | 9.0 | 639 | 0.2335 | 0.4935 | 0.5101 | 0.5016 | 0.9397 | |
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| 0.1436 | 10.0 | 710 | 0.2413 | 0.4829 | 0.5075 | 0.4949 | 0.9405 | |
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| 0.1436 | 11.0 | 781 | 0.2557 | 0.4849 | 0.5239 | 0.5036 | 0.9383 | |
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| 0.1436 | 12.0 | 852 | 0.2557 | 0.4943 | 0.5046 | 0.4994 | 0.9407 | |
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### Framework versions |
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- Transformers 4.35.1 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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