NHS-BiomedNLP-BiomedBERT-hypop-512
This model is a fine-tuned version of microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3839
- Accuracy: 0.8269
- Precision: 0.8228
- Recall: 0.8237
- F1: 0.8232
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: 3e-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: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.124 | 1.0 | 397 | 0.4029 | 0.8177 | 0.8146 | 0.8129 | 0.8137 |
| 0.0594 | 2.0 | 794 | 0.4561 | 0.8246 | 0.8245 | 0.8161 | 0.8192 |
| 0.1105 | 3.0 | 1191 | 0.5390 | 0.8120 | 0.8119 | 0.8028 | 0.8059 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.2+cpu
- Datasets 2.18.0
- Tokenizers 0.15.2
- Downloads last month
- 14
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.