AgitationTextV2
This model is a fine-tuned version of bionlp/bluebert_pubmed_uncased_L-12_H-768_A-12 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6268
- Accuracy: 0.73
- Precision: 0.8036
- Recall: 0.7377
- F1: 0.7692
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 | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.6535 | 1.0 | 50 | 0.6682 | 0.66 | 0.7547 | 0.6557 | 0.7018 |
| 0.5874 | 2.0 | 100 | 0.6695 | 0.66 | 0.7455 | 0.6721 | 0.7069 |
| 0.5373 | 3.0 | 150 | 0.6141 | 0.6 | 0.7838 | 0.4754 | 0.5918 |
| 0.4671 | 4.0 | 200 | 0.6017 | 0.71 | 0.7667 | 0.7541 | 0.7603 |
| 0.4111 | 5.0 | 250 | 0.5507 | 0.75 | 0.8333 | 0.7377 | 0.7826 |
| 0.3828 | 6.0 | 300 | 0.6090 | 0.7 | 0.7541 | 0.7541 | 0.7541 |
| 0.3034 | 7.0 | 350 | 0.6073 | 0.71 | 0.8333 | 0.6557 | 0.7339 |
| 0.2702 | 8.0 | 400 | 0.5790 | 0.71 | 0.8077 | 0.6885 | 0.7434 |
| 0.246 | 9.0 | 450 | 0.7061 | 0.71 | 0.7424 | 0.8033 | 0.7717 |
| 0.2229 | 10.0 | 500 | 0.6268 | 0.73 | 0.8036 | 0.7377 | 0.7692 |
Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1