BioMedRoBERTa-finetuned-ner-pablo-just-classifier
This model is a fine-tuned version of emilyalsentzer/Bio_ClinicalBERT on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1228
- Precision: 0.6701
- Recall: 0.6809
- F1: 0.6754
- Accuracy: 0.9657
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: 0.01
- train_batch_size: 512
- eval_batch_size: 512
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 2048
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 0.9697 | 16 | 0.2938 | 0.4425 | 0.5130 | 0.4751 | 0.9361 |
| No log | 2.0 | 33 | 0.1815 | 0.5546 | 0.5873 | 0.5705 | 0.9535 |
| No log | 2.9697 | 49 | 0.1617 | 0.5838 | 0.6189 | 0.6008 | 0.9575 |
| No log | 4.0 | 66 | 0.1482 | 0.6070 | 0.6396 | 0.6229 | 0.9602 |
| No log | 4.9697 | 82 | 0.1340 | 0.6465 | 0.6563 | 0.6513 | 0.9633 |
| No log | 6.0 | 99 | 0.1306 | 0.6561 | 0.6638 | 0.6599 | 0.9641 |
| No log | 6.9697 | 115 | 0.1290 | 0.6569 | 0.6705 | 0.6636 | 0.9645 |
| No log | 8.0 | 132 | 0.1246 | 0.6664 | 0.6794 | 0.6728 | 0.9654 |
| No log | 8.9697 | 148 | 0.1230 | 0.6699 | 0.6793 | 0.6745 | 0.9656 |
| No log | 9.6970 | 160 | 0.1228 | 0.6701 | 0.6809 | 0.6754 | 0.9657 |
Framework versions
- Transformers 4.44.1
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1