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--- |
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license: apache-2.0 |
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base_model: distilbert-base-uncased |
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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: distilbert-base-uncased-finetuned-ner-cadec-active |
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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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# distilbert-base-uncased-finetuned-ner-cadec-active |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3503 |
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- Precision: 0.4853 |
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- Recall: 0.5067 |
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- F1: 0.4957 |
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- Accuracy: 0.9003 |
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- Adr Precision: 0.4156 |
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- Adr Recall: 0.4971 |
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- Adr F1: 0.4527 |
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- Disease Precision: 0.0 |
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- Disease Recall: 0.0 |
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- Disease F1: 0.0 |
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- Drug Precision: 0.7766 |
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- Drug Recall: 0.8138 |
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- Drug F1: 0.7948 |
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- Finding Precision: 0.0 |
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- Finding Recall: 0.0 |
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- Finding F1: 0.0 |
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- Symptom Precision: 0.0 |
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- Symptom Recall: 0.0 |
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- Symptom F1: 0.0 |
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- B-adr Precision: 0.6582 |
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- B-adr Recall: 0.6551 |
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- B-adr F1: 0.6567 |
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- B-disease Precision: 0.0 |
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- B-disease Recall: 0.0 |
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- B-disease F1: 0.0 |
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- B-drug Precision: 0.9639 |
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- B-drug Recall: 0.8511 |
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- B-drug F1: 0.9040 |
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- B-finding Precision: 0.0 |
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- B-finding Recall: 0.0 |
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- B-finding F1: 0.0 |
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- B-symptom Precision: 0.0 |
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- B-symptom Recall: 0.0 |
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- B-symptom F1: 0.0 |
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- I-adr Precision: 0.4091 |
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- I-adr Recall: 0.4686 |
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- I-adr F1: 0.4368 |
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- I-disease Precision: 0.0 |
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- I-disease Recall: 0.0 |
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- I-disease F1: 0.0 |
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- I-drug Precision: 0.8112 |
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- I-drug Recall: 0.8503 |
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- I-drug F1: 0.8303 |
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- I-finding Precision: 0.0 |
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- I-finding Recall: 0.0 |
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- I-finding F1: 0.0 |
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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: 0.2828 |
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- Weighted Avg F1: 0.5661 |
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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: 10 |
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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 | 24 | 0.7793 | 0.0 | 0.0 | 0.0 | 0.7876 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| No log | 2.0 | 48 | 0.5127 | 0.3553 | 0.2375 | 0.2847 | 0.8510 | 0.2110 | 0.1613 | 0.1829 | 0.0 | 0.0 | 0.0 | 0.9528 | 0.6436 | 0.7683 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9841 | 0.6596 | 0.7898 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0589 | 0.0557 | 0.0572 | 0.0 | 0.0 | 0.0 | 0.9603 | 0.6471 | 0.7732 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1620 | 0.1866 | |
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| No log | 3.0 | 72 | 0.4218 | 0.4082 | 0.3275 | 0.3634 | 0.8659 | 0.3101 | 0.2849 | 0.2970 | 0.0 | 0.0 | 0.0 | 0.8158 | 0.6596 | 0.7294 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6667 | 0.0378 | 0.0715 | 0.0 | 0.0 | 0.0 | 0.9577 | 0.7234 | 0.8242 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1003 | 0.1131 | 0.1063 | 0.0 | 0.0 | 0.0 | 0.8658 | 0.6898 | 0.7679 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1770 | 0.2316 | |
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| No log | 4.0 | 96 | 0.3889 | 0.4168 | 0.3767 | 0.3957 | 0.8763 | 0.3183 | 0.3183 | 0.3183 | 0.0 | 0.0 | 0.0 | 0.7641 | 0.7926 | 0.7781 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6684 | 0.2031 | 0.3116 | 0.0 | 0.0 | 0.0 | 0.95 | 0.8085 | 0.8736 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1453 | 0.1688 | 0.1561 | 0.0 | 0.0 | 0.0 | 0.7824 | 0.8075 | 0.7947 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2136 | 0.3433 | |
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| No log | 5.0 | 120 | 0.3734 | 0.4409 | 0.3859 | 0.4116 | 0.8866 | 0.3450 | 0.3285 | 0.3366 | 0.0 | 0.0 | 0.0 | 0.755 | 0.8032 | 0.7784 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6884 | 0.3165 | 0.4337 | 0.0 | 0.0 | 0.0 | 0.9691 | 0.8351 | 0.8971 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2305 | 0.2442 | 0.2371 | 0.0 | 0.0 | 0.0 | 0.7588 | 0.8075 | 0.7824 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2350 | 0.4149 | |
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| No log | 6.0 | 144 | 0.3626 | 0.4608 | 0.4156 | 0.4370 | 0.8903 | 0.3699 | 0.3721 | 0.3710 | 0.0 | 0.0 | 0.0 | 0.7937 | 0.7979 | 0.7958 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6873 | 0.4016 | 0.5070 | 0.0 | 0.0 | 0.0 | 0.9689 | 0.8298 | 0.8940 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2703 | 0.2926 | 0.2810 | 0.0 | 0.0 | 0.0 | 0.8032 | 0.8075 | 0.8053 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2487 | 0.4579 | |
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| No log | 7.0 | 168 | 0.3535 | 0.4488 | 0.4759 | 0.4620 | 0.8947 | 0.3723 | 0.4491 | 0.4071 | 0.0 | 0.0 | 0.0 | 0.7573 | 0.8298 | 0.7919 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6261 | 0.5827 | 0.6036 | 0.0 | 0.0 | 0.0 | 0.9422 | 0.8670 | 0.9030 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.3303 | 0.3860 | 0.3560 | 0.0 | 0.0 | 0.0 | 0.7843 | 0.8556 | 0.8184 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2681 | 0.5195 | |
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| No log | 8.0 | 192 | 0.3528 | 0.4751 | 0.4985 | 0.4865 | 0.8969 | 0.4055 | 0.4898 | 0.4437 | 0.0 | 0.0 | 0.0 | 0.7732 | 0.7979 | 0.7853 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6410 | 0.6299 | 0.6354 | 0.0 | 0.0 | 0.0 | 0.9636 | 0.8457 | 0.9008 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.3752 | 0.4399 | 0.4050 | 0.0 | 0.0 | 0.0 | 0.7979 | 0.8235 | 0.8105 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2752 | 0.5457 | |
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| No log | 9.0 | 216 | 0.3483 | 0.4822 | 0.5005 | 0.4912 | 0.8984 | 0.4108 | 0.4884 | 0.4462 | 0.0 | 0.0 | 0.0 | 0.7806 | 0.8138 | 0.7969 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6589 | 0.6205 | 0.6391 | 0.0 | 0.0 | 0.0 | 0.9639 | 0.8511 | 0.9040 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.3777 | 0.4434 | 0.4079 | 0.0 | 0.0 | 0.0 | 0.8103 | 0.8449 | 0.8272 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2778 | 0.5501 | |
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| No log | 10.0 | 240 | 0.3503 | 0.4853 | 0.5067 | 0.4957 | 0.9003 | 0.4156 | 0.4971 | 0.4527 | 0.0 | 0.0 | 0.0 | 0.7766 | 0.8138 | 0.7948 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6582 | 0.6551 | 0.6567 | 0.0 | 0.0 | 0.0 | 0.9639 | 0.8511 | 0.9040 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4091 | 0.4686 | 0.4368 | 0.0 | 0.0 | 0.0 | 0.8112 | 0.8503 | 0.8303 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2828 | 0.5661 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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