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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-uncasedfinetuned-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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# distilbert-base-uncased-finetuned-ner-cadec |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4315 |
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- Precision: 0.3648 |
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- Recall: 0.3333 |
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- F1: 0.3483 |
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- Accuracy: 0.8708 |
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- Adr Precision: 0.2667 |
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- Adr Recall: 0.2716 |
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- Adr F1: 0.2691 |
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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: 0.7483 |
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- Drug Recall: 0.6848 |
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- Drug F1: 0.7152 |
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- Finding Precision: 0.25 |
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- Finding Recall: 0.0222 |
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- Finding F1: 0.0408 |
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- Symptom Precision: 0.3333 |
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- Symptom Recall: 0.1852 |
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- Symptom F1: 0.2381 |
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- B-adr Precision: 0.5655 |
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- B-adr Recall: 0.4472 |
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- B-adr F1: 0.4995 |
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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: 0.8768 |
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- B-drug Recall: 0.7333 |
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- B-drug F1: 0.7987 |
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- B-finding Precision: 1.0 |
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- B-finding Recall: 0.0222 |
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- B-finding F1: 0.0435 |
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- B-symptom Precision: 0.4167 |
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- B-symptom Recall: 0.2 |
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- B-symptom F1: 0.2703 |
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- I-adr Precision: 0.2236 |
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- I-adr Recall: 0.2009 |
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- I-adr F1: 0.2117 |
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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: 0.8 |
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- I-drug Recall: 0.6871 |
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- I-drug F1: 0.7393 |
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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: 0.2563 |
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- Weighted Avg F1: 0.4250 |
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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 | 127 | 0.5842 | 0.3290 | 0.1573 | 0.2128 | 0.8274 | 0.1197 | 0.0624 | 0.0820 | 0.0 | 0.0 | 0.0 | 0.9293 | 0.5576 | 0.6970 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4157 | 0.0710 | 0.1213 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0667 | 0.125 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0383 | 0.0203 | 0.0265 | 0.0 | 0.0 | 0.0 | 0.1212 | 0.0736 | 0.0916 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0364 | 0.0764 | |
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| No log | 2.0 | 254 | 0.5137 | 0.2948 | 0.1910 | 0.2318 | 0.8476 | 0.1337 | 0.1028 | 0.1162 | 0.0 | 0.0 | 0.0 | 0.97 | 0.5879 | 0.7321 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4724 | 0.2303 | 0.3097 | 0.0 | 0.0 | 0.0 | 0.9899 | 0.5939 | 0.7424 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1053 | 0.0587 | 0.0754 | 0.0 | 0.0 | 0.0 | 0.97 | 0.5951 | 0.7376 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1865 | 0.3023 | |
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| No log | 3.0 | 381 | 0.4805 | 0.3057 | 0.2022 | 0.2434 | 0.8500 | 0.1487 | 0.1138 | 0.1289 | 0.0 | 0.0 | 0.0 | 0.8850 | 0.6061 | 0.7194 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5417 | 0.1747 | 0.2642 | 0.0 | 0.0 | 0.0 | 0.9623 | 0.6182 | 0.7528 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0851 | 0.0632 | 0.0725 | 0.0 | 0.0 | 0.0 | 0.9252 | 0.6074 | 0.7333 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1823 | 0.2858 | |
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| 0.5965 | 4.0 | 508 | 0.4963 | 0.3717 | 0.2260 | 0.2811 | 0.8570 | 0.2174 | 0.1468 | 0.1752 | 0.0 | 0.0 | 0.0 | 0.8487 | 0.6121 | 0.7113 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5853 | 0.2438 | 0.3442 | 0.0 | 0.0 | 0.0 | 0.9630 | 0.6303 | 0.7619 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1641 | 0.0948 | 0.1202 | 0.0 | 0.0 | 0.0 | 0.9107 | 0.6258 | 0.7418 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1968 | 0.3312 | |
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| 0.5965 | 5.0 | 635 | 0.4448 | 0.3323 | 0.2759 | 0.3015 | 0.8619 | 0.2239 | 0.2165 | 0.2201 | 0.0 | 0.0 | 0.0 | 0.7574 | 0.6242 | 0.6844 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5827 | 0.3109 | 0.4055 | 0.0 | 0.0 | 0.0 | 0.9561 | 0.6606 | 0.7814 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1314 | 0.1219 | 0.1265 | 0.0 | 0.0 | 0.0 | 0.8031 | 0.6258 | 0.7034 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2017 | 0.3531 | |
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| 0.5965 | 6.0 | 762 | 0.4285 | 0.3672 | 0.3021 | 0.3315 | 0.8682 | 0.2553 | 0.2440 | 0.2495 | 0.0 | 0.0 | 0.0 | 0.7970 | 0.6424 | 0.7114 | 0.0 | 0.0 | 0.0 | 0.6 | 0.1111 | 0.1875 | 0.6210 | 0.3743 | 0.4671 | 0.0 | 0.0 | 0.0 | 0.9569 | 0.6727 | 0.7900 | 0.0 | 0.0 | 0.0 | 0.6 | 0.12 | 0.2000 | 0.1641 | 0.1445 | 0.1537 | 0.0 | 0.0 | 0.0 | 0.8254 | 0.6380 | 0.7197 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2330 | 0.3898 | |
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| 0.5965 | 7.0 | 889 | 0.4268 | 0.3582 | 0.3233 | 0.3399 | 0.8701 | 0.2531 | 0.2624 | 0.2577 | 0.0 | 0.0 | 0.0 | 0.7832 | 0.6788 | 0.7273 | 0.0 | 0.0 | 0.0 | 0.4444 | 0.1481 | 0.2222 | 0.5707 | 0.4338 | 0.4929 | 0.0 | 0.0 | 0.0 | 0.9268 | 0.6909 | 0.7917 | 0.0 | 0.0 | 0.0 | 0.5714 | 0.16 | 0.25 | 0.1932 | 0.1783 | 0.1854 | 0.0 | 0.0 | 0.0 | 0.7698 | 0.6564 | 0.7086 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2429 | 0.4087 | |
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| 0.3701 | 8.0 | 1016 | 0.4297 | 0.3723 | 0.3221 | 0.3454 | 0.8725 | 0.2606 | 0.2606 | 0.2606 | 0.0 | 0.0 | 0.0 | 0.8175 | 0.6788 | 0.7417 | 0.0 | 0.0 | 0.0 | 0.5 | 0.1481 | 0.2286 | 0.5805 | 0.4223 | 0.4889 | 0.0 | 0.0 | 0.0 | 0.9370 | 0.7212 | 0.8151 | 0.0 | 0.0 | 0.0 | 0.5714 | 0.16 | 0.25 | 0.2020 | 0.1828 | 0.1919 | 0.0 | 0.0 | 0.0 | 0.8358 | 0.6871 | 0.7542 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2500 | 0.4170 | |
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| 0.3701 | 9.0 | 1143 | 0.4345 | 0.3688 | 0.3333 | 0.3502 | 0.8717 | 0.2648 | 0.2716 | 0.2681 | 0.0 | 0.0 | 0.0 | 0.7958 | 0.6848 | 0.7362 | 0.3333 | 0.0222 | 0.0417 | 0.3571 | 0.1852 | 0.2439 | 0.5566 | 0.4530 | 0.4995 | 0.0 | 0.0 | 0.0 | 0.9023 | 0.7273 | 0.8054 | 1.0 | 0.0222 | 0.0435 | 0.4167 | 0.2 | 0.2703 | 0.2173 | 0.1874 | 0.2012 | 0.0 | 0.0 | 0.0 | 0.8235 | 0.6871 | 0.7492 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2569 | 0.4237 | |
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| 0.3701 | 10.0 | 1270 | 0.4315 | 0.3648 | 0.3333 | 0.3483 | 0.8708 | 0.2667 | 0.2716 | 0.2691 | 0.0 | 0.0 | 0.0 | 0.7483 | 0.6848 | 0.7152 | 0.25 | 0.0222 | 0.0408 | 0.3333 | 0.1852 | 0.2381 | 0.5655 | 0.4472 | 0.4995 | 0.0 | 0.0 | 0.0 | 0.8768 | 0.7333 | 0.7987 | 1.0 | 0.0222 | 0.0435 | 0.4167 | 0.2 | 0.2703 | 0.2236 | 0.2009 | 0.2117 | 0.0 | 0.0 | 0.0 | 0.8 | 0.6871 | 0.7393 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2563 | 0.4250 | |
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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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