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: 0.0909
- Precision: 0.6831
- Recall: 0.7942
- F1: 0.7344
- Accuracy: 0.9787
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 |
|---|---|---|---|---|---|---|---|
| 0.1074 | 1.0 | 679 | 0.0666 | 0.6112 | 0.7891 | 0.6889 | 0.9764 |
| 0.0483 | 2.0 | 1358 | 0.0678 | 0.6894 | 0.8094 | 0.7446 | 0.9793 |
| 0.0136 | 3.0 | 2037 | 0.0909 | 0.6831 | 0.7942 | 0.7344 | 0.9787 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2