---
license: mit
base_model: microsoft/biogpt
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: biogpt-disease-ner
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# biogpt-disease-ner

This model is a fine-tuned version of [microsoft/biogpt](https://huggingface.co/microsoft/biogpt) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1525
- Precision: 0.5241
- Recall: 0.6075
- F1: 0.5628
- Accuracy: 0.9522

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.27          | 1.0   | 593  | 0.1769          | 0.4632    | 0.4523 | 0.4577 | 0.9395   |
| 0.1581        | 2.0   | 1186 | 0.1561          | 0.5337    | 0.5083 | 0.5207 | 0.9475   |
| 0.1225        | 3.0   | 1779 | 0.1525          | 0.5241    | 0.6075 | 0.5628 | 0.9522   |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1