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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: 0.3873 |
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- Precision: 0.4488 |
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- Recall: 0.4483 |
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- F1: 0.4485 |
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- Accuracy: 0.8907 |
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- Adr Precision: 0.3791 |
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- Adr Recall: 0.4375 |
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- Adr F1: 0.4062 |
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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: 0.7527 |
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- Drug Recall: 0.7287 |
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- Drug F1: 0.7405 |
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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: 0.6329 |
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- B-adr Recall: 0.5512 |
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- B-adr F1: 0.5892 |
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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: 0.9718 |
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- B-drug Recall: 0.7340 |
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- B-drug F1: 0.8364 |
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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: 0.3287 |
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- I-adr Recall: 0.3860 |
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- I-adr F1: 0.3551 |
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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: 0.8066 |
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- I-drug Recall: 0.7807 |
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- I-drug F1: 0.7935 |
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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: 0.2574 |
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- Weighted Avg F1: 0.5041 |
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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 | 16 | 0.8554 | 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 | 32 | 0.6110 | 0.1709 | 0.0901 | 0.1180 | 0.8226 | 0.1709 | 0.1279 | 0.1463 | 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 | 0.0699 | 0.0646 | 0.0672 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0067 | 0.0215 | |
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| No log | 3.0 | 48 | 0.5114 | 0.2118 | 0.1433 | 0.1709 | 0.8496 | 0.2612 | 0.2035 | 0.2288 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.55 | 0.0173 | 0.0336 | 0.0 | 0.0 | 0.0 | 0.984 | 0.6543 | 0.7859 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0918 | 0.0880 | 0.0898 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0909 | 0.1259 | |
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| No log | 4.0 | 64 | 0.4618 | 0.4412 | 0.3224 | 0.3726 | 0.8660 | 0.3271 | 0.2791 | 0.3012 | 0.0 | 0.0 | 0.0 | 0.9685 | 0.6543 | 0.7810 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6375 | 0.0803 | 0.1427 | 0.0 | 0.0 | 0.0 | 0.9843 | 0.6649 | 0.7937 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1209 | 0.1257 | 0.1232 | 0.0 | 0.0 | 0.0 | 0.9685 | 0.6578 | 0.7834 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1843 | 0.2613 | |
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| No log | 5.0 | 80 | 0.4254 | 0.4072 | 0.3460 | 0.3741 | 0.8679 | 0.3080 | 0.3125 | 0.3102 | 0.0 | 0.0 | 0.0 | 0.9318 | 0.6543 | 0.7688 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5960 | 0.1858 | 0.2833 | 0.0 | 0.0 | 0.0 | 0.9843 | 0.6649 | 0.7937 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1381 | 0.1652 | 0.1504 | 0.0 | 0.0 | 0.0 | 0.9394 | 0.6631 | 0.7774 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2005 | 0.3207 | |
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| No log | 6.0 | 96 | 0.4048 | 0.4377 | 0.4063 | 0.4214 | 0.8835 | 0.3634 | 0.3983 | 0.3800 | 0.0 | 0.0 | 0.0 | 0.8039 | 0.6543 | 0.7214 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6335 | 0.4409 | 0.5200 | 0.0 | 0.0 | 0.0 | 0.9766 | 0.6649 | 0.7911 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2772 | 0.3250 | 0.2992 | 0.0 | 0.0 | 0.0 | 0.8618 | 0.7005 | 0.7729 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2383 | 0.4538 | |
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| No log | 7.0 | 112 | 0.3952 | 0.4114 | 0.3920 | 0.4015 | 0.8815 | 0.3303 | 0.3663 | 0.3473 | 0.0 | 0.0 | 0.0 | 0.7798 | 0.6968 | 0.7360 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6121 | 0.4126 | 0.4929 | 0.0 | 0.0 | 0.0 | 0.9784 | 0.7234 | 0.8318 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2394 | 0.2926 | 0.2633 | 0.0 | 0.0 | 0.0 | 0.8383 | 0.7487 | 0.7910 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2379 | 0.4388 | |
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| No log | 8.0 | 128 | 0.3922 | 0.4575 | 0.4411 | 0.4492 | 0.8884 | 0.3821 | 0.4331 | 0.4060 | 0.0 | 0.0 | 0.0 | 0.8210 | 0.7074 | 0.76 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6331 | 0.5354 | 0.5802 | 0.0 | 0.0 | 0.0 | 0.9784 | 0.7234 | 0.8318 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.3281 | 0.3788 | 0.3517 | 0.0 | 0.0 | 0.0 | 0.8758 | 0.7540 | 0.8103 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2574 | 0.5010 | |
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| No log | 9.0 | 144 | 0.3886 | 0.4549 | 0.4391 | 0.4469 | 0.8887 | 0.3815 | 0.4259 | 0.4025 | 0.0 | 0.0 | 0.0 | 0.7771 | 0.7234 | 0.7493 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6271 | 0.5244 | 0.5712 | 0.0 | 0.0 | 0.0 | 0.9716 | 0.7287 | 0.8328 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.3297 | 0.3770 | 0.3518 | 0.0 | 0.0 | 0.0 | 0.8333 | 0.7754 | 0.8033 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2559 | 0.4971 | |
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| No log | 10.0 | 160 | 0.3873 | 0.4488 | 0.4483 | 0.4485 | 0.8907 | 0.3791 | 0.4375 | 0.4062 | 0.0 | 0.0 | 0.0 | 0.7527 | 0.7287 | 0.7405 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6329 | 0.5512 | 0.5892 | 0.0 | 0.0 | 0.0 | 0.9718 | 0.7340 | 0.8364 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.3287 | 0.3860 | 0.3551 | 0.0 | 0.0 | 0.0 | 0.8066 | 0.7807 | 0.7935 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2574 | 0.5041 | |
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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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