metadata
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: biobert-base-cased-v1.2-finetuned-ner-CRAFT_Augmented_ES
results: []
biobert-base-cased-v1.2-finetuned-ner-CRAFT_Augmented_ES
This model is a fine-tuned version of dmis-lab/biobert-base-cased-v1.2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2251
- Precision: 0.8276
- Recall: 0.8411
- F1: 0.8343
- Accuracy: 0.9676
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.0549 | 1.0 | 4078 | 0.1673 | 0.8056 | 0.8112 | 0.8084 | 0.9640 |
0.0233 | 2.0 | 8156 | 0.1733 | 0.8321 | 0.8244 | 0.8283 | 0.9662 |
0.0101 | 3.0 | 12234 | 0.1972 | 0.8336 | 0.8391 | 0.8363 | 0.9678 |
0.0036 | 4.0 | 16312 | 0.2251 | 0.8276 | 0.8411 | 0.8343 | 0.9676 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6