nci-ner-v2-stage-a
This model is a fine-tuned version of FacebookAI/roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0730
- Precision: 0.8738
- Recall: 0.9052
- F1: 0.8892
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: 32
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 |
|---|---|---|---|---|---|---|
| 0.1492 | 0.5339 | 500 | 0.1215 | 0.7791 | 0.7827 | 0.7809 |
| 0.0893 | 1.0678 | 1000 | 0.0935 | 0.8005 | 0.8559 | 0.8273 |
| 0.0763 | 1.6017 | 1500 | 0.0861 | 0.8284 | 0.8707 | 0.8490 |
| 0.0593 | 2.1356 | 2000 | 0.0821 | 0.8435 | 0.8783 | 0.8605 |
| 0.0492 | 2.6695 | 2500 | 0.0893 | 0.8343 | 0.8818 | 0.8574 |
| 0.0423 | 3.2034 | 3000 | 0.0819 | 0.8570 | 0.8857 | 0.8712 |
| 0.0379 | 3.7373 | 3500 | 0.0832 | 0.8562 | 0.8900 | 0.8728 |
| 0.0359 | 4.2712 | 4000 | 0.0851 | 0.8535 | 0.8913 | 0.8720 |
| 0.0386 | 4.8051 | 4500 | 0.0838 | 0.8555 | 0.8917 | 0.8732 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.10.0+cu128
- Datasets 2.21.0
- Tokenizers 0.20.3