metadata
tags:
- generated_from_trainer
datasets:
- ncbi_disease
metrics:
- precision
- recall
- f1
- accuracy
model_index:
- name: biobert_v1.1_pubmed-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: ncbi_disease
type: ncbi_disease
args: ncbi_disease
metric:
name: Accuracy
type: accuracy
value: 0.9827274990663513
biobert_v1.1_pubmed-finetuned-ner
This model is a fine-tuned version of monologg/biobert_v1.1_pubmed on the ncbi_disease dataset. It achieves the following results on the evaluation set:
- Loss: 0.0657
- Precision: 0.8338
- Recall: 0.8933
- F1: 0.8625
- Accuracy: 0.9827
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 | 340 | 0.0612 | 0.8268 | 0.85 | 0.8382 | 0.9806 |
| 0.0987 | 2.0 | 680 | 0.0604 | 0.8397 | 0.8848 | 0.8616 | 0.9829 |
| 0.0272 | 3.0 | 1020 | 0.0657 | 0.8338 | 0.8933 | 0.8625 | 0.9827 |
Framework versions
- Transformers 4.8.1
- Pytorch 1.9.0
- Datasets 1.6.2
- Tokenizers 0.10.3