metadata
license: mit
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: AgitationNotesClassification
results: []
AgitationNotesClassification
This model is a fine-tuned version of emilyalsentzer/Bio_ClinicalBERT on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4128
- F1: 0.8690
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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 0.6567 | 1.0 | 50 | 0.6130 | 0.6500 |
| 0.6056 | 2.0 | 100 | 0.5807 | 0.6763 |
| 0.5172 | 3.0 | 150 | 0.5398 | 0.6675 |
| 0.4206 | 4.0 | 200 | 0.4111 | 0.8355 |
| 0.3361 | 5.0 | 250 | 0.3977 | 0.8667 |
| 0.2919 | 6.0 | 300 | 0.3874 | 0.8780 |
| 0.2233 | 7.0 | 350 | 0.3928 | 0.8690 |
| 0.1953 | 8.0 | 400 | 0.3908 | 0.8690 |
| 0.1633 | 9.0 | 450 | 0.4076 | 0.86 |
| 0.1494 | 10.0 | 500 | 0.4128 | 0.8690 |
Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1