Medical-NER-2026-Success
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9188
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 4 | 1.5839 |
| 1.8456 | 2.0 | 8 | 1.2376 |
| 1.2603 | 3.0 | 12 | 1.0594 |
| 0.9737 | 4.0 | 16 | 0.9637 |
| 0.8411 | 5.0 | 20 | 0.9188 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cpu
- Datasets 4.8.3
- Tokenizers 0.22.2
- Downloads last month
- 18
Model tree for sohaibdevv/Medical-NER-2026-Success
Base model
distilbert/distilbert-base-uncased