metadata
license: cc0-1.0
base_model: bionlp/bluebert_pubmed_mimic_uncased_L-12_H-768_A-12
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BlueBERT_BioNLP13CG_NER
results: []
BlueBERT_BioNLP13CG_NER
This model is a fine-tuned version of bionlp/bluebert_pubmed_mimic_uncased_L-12_H-768_A-12 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2929
- Precision: 0.9311
- Recall: 0.9373
- F1: 0.9342
- Accuracy: 0.9309
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
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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 | 0.99 | 95 | 0.4398 | 0.8891 | 0.8989 | 0.8940 | 0.8876 |
| No log | 2.0 | 191 | 0.3148 | 0.9259 | 0.9325 | 0.9292 | 0.9252 |
| No log | 2.98 | 285 | 0.2929 | 0.9311 | 0.9373 | 0.9342 | 0.9309 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0