--- license: apache-2.0 base_model: google/electra-small-discriminator tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: electra-small-discriminator-finetuned-ner-cadec results: [] --- # electra-small-discriminator-finetuned-ner-cadec This model is a fine-tuned version of [google/electra-small-discriminator](https://huggingface.co/google/electra-small-discriminator) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.3089 - Precision: 0.5240 - Recall: 0.6280 - F1: 0.5713 - Accuracy: 0.9120 - Adr Precision: 0.4580 - Adr Recall: 0.6495 - Adr F1: 0.5372 - Disease Precision: 0.0 - Disease Recall: 0.0 - Disease F1: 0.0 - Drug Precision: 0.8187 - Drug Recall: 0.9030 - Drug F1: 0.8588 - Finding Precision: 0.0 - Finding Recall: 0.0 - Finding F1: 0.0 - Symptom Precision: 0.0 - Symptom Recall: 0.0 - Symptom F1: 0.0 - B-adr Precision: 0.6345 - B-adr Recall: 0.8196 - B-adr F1: 0.7152 - B-disease Precision: 0.0 - B-disease Recall: 0.0 - B-disease F1: 0.0 - B-drug Precision: 0.8902 - B-drug Recall: 0.9333 - B-drug F1: 0.9112 - B-finding Precision: 0.0 - B-finding Recall: 0.0 - B-finding F1: 0.0 - B-symptom Precision: 0.0 - B-symptom Recall: 0.0 - B-symptom F1: 0.0 - I-adr Precision: 0.4753 - I-adr Recall: 0.6380 - I-adr F1: 0.5448 - I-disease Precision: 0.0 - I-disease Recall: 0.0 - I-disease F1: 0.0 - I-drug Precision: 0.8371 - I-drug Recall: 0.9030 - I-drug F1: 0.8688 - I-finding Precision: 0.6667 - I-finding Recall: 0.0625 - I-finding F1: 0.1143 - I-symptom Precision: 0.0 - I-symptom Recall: 0.0 - I-symptom F1: 0.0 - Macro Avg F1: 0.3154 - Weighted Avg F1: 0.6288 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 10 ### Training results | 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 | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:-------------:|:----------:|:------:|:-----------------:|:--------------:|:----------:|:--------------:|:-----------:|:-------:|:-----------------:|:--------------:|:----------:|:-----------------:|:--------------:|:----------:|:---------------:|:------------:|:--------:|:-------------------:|:----------------:|:------------:|:----------------:|:-------------:|:---------:|:-------------------:|:----------------:|:------------:|:-------------------:|:----------------:|:------------:|:---------------:|:------------:|:--------:|:-------------------:|:----------------:|:------------:|:----------------:|:-------------:|:---------:|:-------------------:|:----------------:|:------------:|:-------------------:|:----------------:|:------------:|:------------:|:---------------:| | No log | 1.0 | 127 | 0.5920 | 0.2042 | 0.1710 | 0.1861 | 0.8334 | 0.2042 | 0.2514 | 0.2253 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1667 | 0.0038 | 0.0075 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0238 | 0.0353 | 0.0285 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0036 | 0.0115 | | No log | 2.0 | 254 | 0.4272 | 0.4122 | 0.4806 | 0.4438 | 0.8895 | 0.3547 | 0.5376 | 0.4274 | 0.0 | 0.0 | 0.0 | 0.8519 | 0.5576 | 0.6740 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5794 | 0.7351 | 0.6481 | 0.0 | 0.0 | 0.0 | 0.9709 | 0.6061 | 0.7463 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.3556 | 0.5055 | 0.4175 | 0.0 | 0.0 | 0.0 | 0.9588 | 0.5636 | 0.7099 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2522 | 0.5261 | | No log | 3.0 | 381 | 0.3799 | 0.4580 | 0.5918 | 0.5163 | 0.8982 | 0.4002 | 0.6294 | 0.4893 | 0.0 | 0.0 | 0.0 | 0.7360 | 0.7939 | 0.7638 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5794 | 0.7985 | 0.6715 | 0.0 | 0.0 | 0.0 | 0.8758 | 0.8545 | 0.8650 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4018 | 0.5960 | 0.4800 | 0.0 | 0.0 | 0.0 | 0.7870 | 0.8061 | 0.7964 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2813 | 0.5771 | | 0.6133 | 4.0 | 508 | 0.3578 | 0.4755 | 0.6067 | 0.5332 | 0.9007 | 0.4097 | 0.6330 | 0.4975 | 0.0 | 0.0 | 0.0 | 0.7833 | 0.8545 | 0.8174 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5840 | 0.8273 | 0.6847 | 0.0 | 0.0 | 0.0 | 0.8862 | 0.8970 | 0.8916 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4169 | 0.6093 | 0.4951 | 0.0 | 0.0 | 0.0 | 0.8372 | 0.8727 | 0.8546 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2926 | 0.5961 | | 0.6133 | 5.0 | 635 | 0.3254 | 0.5124 | 0.6180 | 0.5603 | 0.9079 | 0.4476 | 0.6422 | 0.5275 | 0.0 | 0.0 | 0.0 | 0.7880 | 0.8788 | 0.8309 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6197 | 0.8100 | 0.7022 | 0.0 | 0.0 | 0.0 | 0.8613 | 0.9030 | 0.8817 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4663 | 0.6269 | 0.5348 | 0.0 | 0.0 | 0.0 | 0.8066 | 0.8848 | 0.8439 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2963 | 0.6124 | | 0.6133 | 6.0 | 762 | 0.3153 | 0.5272 | 0.6180 | 0.5690 | 0.9114 | 0.4624 | 0.6422 | 0.5376 | 0.0 | 0.0 | 0.0 | 0.7967 | 0.8788 | 0.8357 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6353 | 0.8023 | 0.7091 | 0.0 | 0.0 | 0.0 | 0.8779 | 0.9152 | 0.8961 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4649 | 0.6137 | 0.5290 | 0.0 | 0.0 | 0.0 | 0.8249 | 0.8848 | 0.8538 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2988 | 0.6158 | | 0.6133 | 7.0 | 889 | 0.3095 | 0.5341 | 0.6155 | 0.5719 | 0.9126 | 0.4658 | 0.6367 | 0.5380 | 0.0 | 0.0 | 0.0 | 0.8202 | 0.8848 | 0.8513 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6453 | 0.7927 | 0.7115 | 0.0 | 0.0 | 0.0 | 0.8935 | 0.9152 | 0.9042 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4714 | 0.6181 | 0.5349 | 0.0 | 0.0 | 0.0 | 0.8448 | 0.8909 | 0.8673 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.3018 | 0.6209 | | 0.3074 | 8.0 | 1016 | 0.3080 | 0.5292 | 0.6217 | 0.5718 | 0.9121 | 0.4604 | 0.6404 | 0.5357 | 0.0 | 0.0 | 0.0 | 0.8324 | 0.9030 | 0.8663 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6397 | 0.8042 | 0.7126 | 0.0 | 0.0 | 0.0 | 0.8947 | 0.9273 | 0.9107 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4792 | 0.6358 | 0.5465 | 0.0 | 0.0 | 0.0 | 0.8418 | 0.9030 | 0.8713 | 0.5 | 0.0312 | 0.0588 | 0.0 | 0.0 | 0.0 | 0.3100 | 0.6274 | | 0.3074 | 9.0 | 1143 | 0.3072 | 0.5225 | 0.6230 | 0.5683 | 0.9119 | 0.4583 | 0.6459 | 0.5362 | 0.0 | 0.0 | 0.0 | 0.8077 | 0.8909 | 0.8473 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6415 | 0.8138 | 0.7174 | 0.0 | 0.0 | 0.0 | 0.8882 | 0.9152 | 0.9015 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4690 | 0.6336 | 0.5390 | 0.0 | 0.0 | 0.0 | 0.8362 | 0.8970 | 0.8655 | 0.3333 | 0.0312 | 0.0571 | 0.0 | 0.0 | 0.0 | 0.3081 | 0.6250 | | 0.3074 | 10.0 | 1270 | 0.3089 | 0.5240 | 0.6280 | 0.5713 | 0.9120 | 0.4580 | 0.6495 | 0.5372 | 0.0 | 0.0 | 0.0 | 0.8187 | 0.9030 | 0.8588 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6345 | 0.8196 | 0.7152 | 0.0 | 0.0 | 0.0 | 0.8902 | 0.9333 | 0.9112 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4753 | 0.6380 | 0.5448 | 0.0 | 0.0 | 0.0 | 0.8371 | 0.9030 | 0.8688 | 0.6667 | 0.0625 | 0.1143 | 0.0 | 0.0 | 0.0 | 0.3154 | 0.6288 | ### Framework versions - Transformers 4.35.2 - Pytorch 2.1.0+cu118 - Datasets 2.15.0 - Tokenizers 0.15.0