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--- |
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license: apache-2.0 |
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base_model: bert-base-cased |
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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: bert-finetuned-ner-cadec |
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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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# bert-finetuned-ner-cadec |
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This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2334 |
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- Precision: 0.6055 |
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- Recall: 0.6988 |
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- F1: 0.6488 |
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- Accuracy: 0.9250 |
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- Adr Precision: 0.5685 |
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- Adr Recall: 0.6992 |
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- Adr F1: 0.6271 |
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- Disease Precision: 0.25 |
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- Disease Recall: 0.125 |
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- Disease F1: 0.1667 |
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- Drug Precision: 0.8371 |
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- Drug Recall: 0.9069 |
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- Drug F1: 0.8706 |
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- Finding Precision: 0.2439 |
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- Finding Recall: 0.3448 |
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- Finding F1: 0.2857 |
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- Symptom Precision: 0.5 |
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- Symptom Recall: 0.0870 |
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- Symptom F1: 0.1481 |
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- B-adr Precision: 0.7596 |
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- B-adr Recall: 0.8357 |
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- B-adr F1: 0.7958 |
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- B-disease Precision: 0.6 |
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- B-disease Recall: 0.1875 |
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- B-disease F1: 0.2857 |
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- B-drug Precision: 0.9423 |
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- B-drug Recall: 0.9655 |
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- B-drug F1: 0.9538 |
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- B-finding Precision: 0.5789 |
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- B-finding Recall: 0.3793 |
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- B-finding F1: 0.4583 |
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- B-symptom Precision: 0.5 |
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- B-symptom Recall: 0.0870 |
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- B-symptom F1: 0.1481 |
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- I-adr Precision: 0.5699 |
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- I-adr Recall: 0.6782 |
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- I-adr F1: 0.6194 |
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- I-disease Precision: 0.3333 |
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- I-disease Recall: 0.1379 |
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- I-disease F1: 0.1951 |
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- I-drug Precision: 0.8611 |
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- I-drug Recall: 0.9118 |
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- I-drug F1: 0.8857 |
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- I-finding Precision: 0.3125 |
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- I-finding Recall: 0.3704 |
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- I-finding F1: 0.3390 |
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- I-symptom Precision: 0.0 |
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- I-symptom Recall: 0.0 |
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- I-symptom F1: 0.0 |
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- Macro Avg F1: 0.4681 |
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- Weighted Avg F1: 0.7238 |
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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: 2e-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: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | Adr Precision | Adr Recall | Adr F1 | Disease Precision | Disease Recall | Disease F1 | Drug Precision | Drug Recall | Drug F1 | Finding Precision | Finding Recall | Finding F1 | Symptom Precision | Symptom Recall | Symptom F1 | B-adr Precision | B-adr Recall | B-adr F1 | B-disease Precision | B-disease Recall | B-disease F1 | B-drug Precision | B-drug Recall | B-drug F1 | B-finding Precision | B-finding Recall | B-finding F1 | B-symptom Precision | B-symptom Recall | B-symptom F1 | I-adr Precision | I-adr Recall | I-adr F1 | I-disease Precision | I-disease Recall | I-disease F1 | I-drug Precision | I-drug Recall | I-drug F1 | I-finding Precision | I-finding Recall | I-finding F1 | I-symptom Precision | I-symptom Recall | I-symptom F1 | Macro Avg F1 | Weighted Avg F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:-------------:|:----------:|:------:|:-----------------:|:--------------:|:----------:|:--------------:|:-----------:|:-------:|:-----------------:|:--------------:|:----------:|:-----------------:|:--------------:|:----------:|:---------------:|:------------:|:--------:|:-------------------:|:----------------:|:------------:|:----------------:|:-------------:|:---------:|:-------------------:|:----------------:|:------------:|:-------------------:|:----------------:|:------------:|:---------------:|:------------:|:--------:|:-------------------:|:----------------:|:------------:|:----------------:|:-------------:|:---------:|:-------------------:|:----------------:|:------------:|:-------------------:|:----------------:|:------------:|:------------:|:---------------:| |
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| No log | 1.0 | 127 | 0.2633 | 0.5612 | 0.6348 | 0.5958 | 0.9139 | 0.5047 | 0.6436 | 0.5658 | 0.0 | 0.0 | 0.0 | 0.8148 | 0.8627 | 0.8381 | 0.0714 | 0.0345 | 0.0465 | 0.0 | 0.0 | 0.0 | 0.7530 | 0.7778 | 0.7652 | 0.0 | 0.0 | 0.0 | 0.9154 | 0.9064 | 0.9109 | 1.0 | 0.0690 | 0.1290 | 0.0 | 0.0 | 0.0 | 0.4993 | 0.6362 | 0.5595 | 0.0 | 0.0 | 0.0 | 0.8775 | 0.8775 | 0.8775 | 0.3077 | 0.1481 | 0.2 | 0.0 | 0.0 | 0.0 | 0.3442 | 0.6698 | |
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| No log | 2.0 | 254 | 0.2358 | 0.6 | 0.6863 | 0.6402 | 0.9240 | 0.5595 | 0.6857 | 0.6162 | 0.2222 | 0.125 | 0.16 | 0.8296 | 0.9069 | 0.8665 | 0.2647 | 0.3103 | 0.2857 | 0.0 | 0.0 | 0.0 | 0.7649 | 0.8247 | 0.7937 | 0.8333 | 0.1562 | 0.2632 | 0.9327 | 0.9557 | 0.9440 | 0.7222 | 0.4483 | 0.5532 | 0.0 | 0.0 | 0.0 | 0.5646 | 0.6709 | 0.6132 | 0.2222 | 0.1379 | 0.1702 | 0.8664 | 0.9216 | 0.8931 | 0.28 | 0.2593 | 0.2692 | 0.0 | 0.0 | 0.0 | 0.4500 | 0.7185 | |
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| No log | 3.0 | 381 | 0.2334 | 0.6055 | 0.6988 | 0.6488 | 0.9250 | 0.5685 | 0.6992 | 0.6271 | 0.25 | 0.125 | 0.1667 | 0.8371 | 0.9069 | 0.8706 | 0.2439 | 0.3448 | 0.2857 | 0.5 | 0.0870 | 0.1481 | 0.7596 | 0.8357 | 0.7958 | 0.6 | 0.1875 | 0.2857 | 0.9423 | 0.9655 | 0.9538 | 0.5789 | 0.3793 | 0.4583 | 0.5 | 0.0870 | 0.1481 | 0.5699 | 0.6782 | 0.6194 | 0.3333 | 0.1379 | 0.1951 | 0.8611 | 0.9118 | 0.8857 | 0.3125 | 0.3704 | 0.3390 | 0.0 | 0.0 | 0.0 | 0.4681 | 0.7238 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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