elopezlopez/Bio_ClinicalBERT_fold_2_binary_v1

1---2license: mit3tags:4- generated_from_trainer5metrics:6- f17model-index:8- name: Bio_ClinicalBERT_fold_2_binary_v19  results: []10---11 12<!-- This model card has been generated automatically according to the information the Trainer had access to. You13should probably proofread and complete it, then remove this comment. -->14 15# Bio_ClinicalBERT_fold_2_binary_v116 17This model is a fine-tuned version of [emilyalsentzer/Bio_ClinicalBERT](https://huggingface.co/emilyalsentzer/Bio_ClinicalBERT) on the None dataset.18It achieves the following results on the evaluation set:19- Loss: 1.931720- F1: 0.792121 22## Model description23 24More information needed25 26## Intended uses & limitations27 28More information needed29 30## Training and evaluation data31 32More information needed33 34## Training procedure35 36### Training hyperparameters37 38The following hyperparameters were used during training:39- learning_rate: 2e-0540- train_batch_size: 1641- eval_batch_size: 1642- seed: 4243- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-0844- lr_scheduler_type: linear45- num_epochs: 2546 47### Training results48 49| Training Loss | Epoch | Step | Validation Loss | F1     |50|:-------------:|:-----:|:----:|:---------------:|:------:|51| No log        | 1.0   | 290  | 0.4221          | 0.7856 |52| 0.4062        | 2.0   | 580  | 0.5184          | 0.7949 |53| 0.4062        | 3.0   | 870  | 0.6854          | 0.7840 |54| 0.1775        | 4.0   | 1160 | 0.9834          | 0.7840 |55| 0.1775        | 5.0   | 1450 | 1.3223          | 0.7804 |56| 0.0697        | 6.0   | 1740 | 1.2896          | 0.7923 |57| 0.0265        | 7.0   | 2030 | 1.4620          | 0.7914 |58| 0.0265        | 8.0   | 2320 | 1.5554          | 0.7835 |59| 0.0102        | 9.0   | 2610 | 1.7009          | 0.7880 |60| 0.0102        | 10.0  | 2900 | 1.6163          | 0.7923 |61| 0.015         | 11.0  | 3190 | 1.6851          | 0.7841 |62| 0.015         | 12.0  | 3480 | 1.7493          | 0.7901 |63| 0.0141        | 13.0  | 3770 | 1.8819          | 0.7827 |64| 0.0133        | 14.0  | 4060 | 1.7535          | 0.7939 |65| 0.0133        | 15.0  | 4350 | 1.6613          | 0.7966 |66| 0.0067        | 16.0  | 4640 | 1.6807          | 0.7999 |67| 0.0067        | 17.0  | 4930 | 1.6703          | 0.7978 |68| 0.0053        | 18.0  | 5220 | 1.7309          | 0.8013 |69| 0.0037        | 19.0  | 5510 | 1.8058          | 0.7942 |70| 0.0037        | 20.0  | 5800 | 1.8233          | 0.7916 |71| 0.0023        | 21.0  | 6090 | 1.8206          | 0.7913 |72| 0.0023        | 22.0  | 6380 | 1.8466          | 0.7949 |73| 0.0012        | 23.0  | 6670 | 1.8531          | 0.7985 |74| 0.0012        | 24.0  | 6960 | 1.9211          | 0.7944 |75| 0.0001        | 25.0  | 7250 | 1.9317          | 0.7921 |76 77 78### Framework versions79 80- Transformers 4.21.081- Pytorch 1.12.0+cu11382- Datasets 2.4.083- Tokenizers 0.12.184