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

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# bioGPT_finetuned_ncbi

This model is a fine-tuned version of [microsoft/biogpt](https://huggingface.co/microsoft/biogpt) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2107
- Precision: 0.5162
- Recall: 0.5990
- F1: 0.5545
- Accuracy: 0.9533

## 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: 4
- eval_batch_size: 4
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0935        | 1.0   | 1358 | 0.2175          | 0.4239    | 0.5365 | 0.4736 | 0.9486   |
| 0.0585        | 2.0   | 2716 | 0.2052          | 0.4431    | 0.5927 | 0.5071 | 0.9490   |
| 0.0416        | 3.0   | 4074 | 0.2107          | 0.5162    | 0.5990 | 0.5545 | 0.9533   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2