SciBERT_BC5CDR_NER_new
This model is a fine-tuned version of allenai/scibert_scivocab_uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0868
- Precision: 0.9785
- Recall: 0.9771
- F1: 0.9778
- Accuracy: 0.9755
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: 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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 286 | 0.0907 | 0.9766 | 0.9681 | 0.9724 | 0.9687 |
| 0.1007 | 2.0 | 572 | 0.0834 | 0.9784 | 0.9737 | 0.9761 | 0.9735 |
| 0.1007 | 3.0 | 858 | 0.0868 | 0.9785 | 0.9771 | 0.9778 | 0.9755 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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Model tree for judithrosell/SciBERT_BC5CDR_NER_new
Base model
allenai/scibert_scivocab_uncased