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electra-base-discriminator-finetuned-ner-cadec

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+ ---
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+ license: apache-2.0
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+ base_model: google/electra-base-discriminator
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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: electra-base-discriminator-finetuned-ner-cadec
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+ results: []
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+ ---
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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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+
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+ # electra-base-discriminator-finetuned-ner-cadec
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+
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+ This model is a fine-tuned version of [google/electra-base-discriminator](https://huggingface.co/google/electra-base-discriminator) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4364
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+ - Precision: 0.3437
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+ - Recall: 0.2772
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+ - F1: 0.3068
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+ - Accuracy: 0.8714
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+ - Adr Precision: 0.2406
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+ - Adr Recall: 0.2220
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+ - Adr F1: 0.2309
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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: 0.7063
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+ - Drug Recall: 0.6121
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+ - Drug F1: 0.6558
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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: 0.5426
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+ - B-adr Recall: 0.3666
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+ - B-adr F1: 0.4376
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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: 0.9375
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+ - B-drug Recall: 0.6364
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+ - B-drug F1: 0.7581
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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: 0.1906
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+ - I-adr Recall: 0.1738
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+ - I-adr F1: 0.1818
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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: 0.7343
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+ - I-drug Recall: 0.6442
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+ - I-drug F1: 0.6863
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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: 0.2064
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+ - Weighted Avg F1: 0.3770
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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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 | 0.8387 | 0.0 | 0.0 | 0.0 | 0.7902 | 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 | 254 | 0.8358 | 0.0 | 0.0 | 0.0 | 0.7902 | 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 | 3.0 | 381 | 0.7415 | 0.0782 | 0.0512 | 0.0619 | 0.7906 | 0.0782 | 0.0752 | 0.0767 | 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 | 0.0172 | 0.0203 | 0.0186 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0019 | 0.0057 |
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+ | 0.8638 | 4.0 | 508 | 0.6493 | 0.1417 | 0.0637 | 0.0879 | 0.8160 | 0.1417 | 0.0936 | 0.1127 | 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 | 0.0253 | 0.0203 | 0.0225 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0023 | 0.0069 |
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+ | 0.8638 | 5.0 | 635 | 0.5528 | 0.3498 | 0.2122 | 0.2642 | 0.8489 | 0.2037 | 0.1431 | 0.1681 | 0.0 | 0.0 | 0.0 | 0.8932 | 0.5576 | 0.6866 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5104 | 0.0940 | 0.1588 | 0.0 | 0.0 | 0.0 | 0.9444 | 0.4121 | 0.5738 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0760 | 0.0587 | 0.0662 | 0.0 | 0.0 | 0.0 | 0.68 | 0.4172 | 0.5171 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1316 | 0.2012 |
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+ | 0.8638 | 6.0 | 762 | 0.4846 | 0.2864 | 0.2310 | 0.2557 | 0.8587 | 0.1698 | 0.1670 | 0.1684 | 0.0 | 0.0 | 0.0 | 0.8545 | 0.5697 | 0.6836 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5070 | 0.2764 | 0.3578 | 0.0 | 0.0 | 0.0 | 0.9604 | 0.5879 | 0.7293 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1170 | 0.1151 | 0.1160 | 0.0 | 0.0 | 0.0 | 0.8818 | 0.5951 | 0.7106 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1914 | 0.3276 |
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+ | 0.8638 | 7.0 | 889 | 0.4610 | 0.3376 | 0.2622 | 0.2952 | 0.8679 | 0.2253 | 0.2092 | 0.2169 | 0.0 | 0.0 | 0.0 | 0.8276 | 0.5818 | 0.6833 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5228 | 0.2860 | 0.3697 | 0.0 | 0.0 | 0.0 | 0.9519 | 0.6 | 0.7361 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1734 | 0.1648 | 0.1690 | 0.0 | 0.0 | 0.0 | 0.8696 | 0.6135 | 0.7194 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1994 | 0.3498 |
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+ | 0.5419 | 8.0 | 1016 | 0.4499 | 0.2983 | 0.2697 | 0.2833 | 0.8656 | 0.1976 | 0.2128 | 0.2049 | 0.0 | 0.0 | 0.0 | 0.7299 | 0.6061 | 0.6623 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4803 | 0.3743 | 0.4207 | 0.0 | 0.0 | 0.0 | 0.9369 | 0.6303 | 0.7536 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1738 | 0.1828 | 0.1782 | 0.0 | 0.0 | 0.0 | 0.7518 | 0.6319 | 0.6867 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2039 | 0.3693 |
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+ | 0.5419 | 9.0 | 1143 | 0.4511 | 0.3544 | 0.2734 | 0.3087 | 0.8700 | 0.2418 | 0.2165 | 0.2285 | 0.0 | 0.0 | 0.0 | 0.7769 | 0.6121 | 0.6847 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5203 | 0.3436 | 0.4139 | 0.0 | 0.0 | 0.0 | 0.9211 | 0.6364 | 0.7527 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2041 | 0.1783 | 0.1904 | 0.0 | 0.0 | 0.0 | 0.7907 | 0.6258 | 0.6986 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2056 | 0.3718 |
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+ | 0.5419 | 10.0 | 1270 | 0.4364 | 0.3437 | 0.2772 | 0.3068 | 0.8714 | 0.2406 | 0.2220 | 0.2309 | 0.0 | 0.0 | 0.0 | 0.7063 | 0.6121 | 0.6558 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5426 | 0.3666 | 0.4376 | 0.0 | 0.0 | 0.0 | 0.9375 | 0.6364 | 0.7581 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1906 | 0.1738 | 0.1818 | 0.0 | 0.0 | 0.0 | 0.7343 | 0.6442 | 0.6863 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2064 | 0.3770 |
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+
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+
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+ ### Framework versions
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+
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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