metadata
license: mit
base_model: microsoft/biogpt
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner
results: []
bert-finetuned-ner
This model is a fine-tuned version of microsoft/biogpt on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0922
- Precision: 0.6758
- Recall: 0.7814
- F1: 0.7248
- Accuracy: 0.9791
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: 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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1026 | 1.0 | 679 | 0.0663 | 0.6242 | 0.7853 | 0.6956 | 0.9772 |
| 0.0487 | 2.0 | 1358 | 0.0710 | 0.6842 | 0.8094 | 0.7416 | 0.9789 |
| 0.014 | 3.0 | 2037 | 0.0922 | 0.6758 | 0.7814 | 0.7248 | 0.9791 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2