---
license: mit
base_model: microsoft/biogpt
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: MLMA-Lab8-FinetunedBioGPT
  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. -->

# MLMA-Lab8-FinetunedBioGPT

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: 0.1455
- Precision: 0.4466
- Recall: 0.5476
- F1: 0.4920
- Accuracy: 0.9579

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.3067        | 1.0   | 679  | 0.1668          | 0.3167    | 0.4358 | 0.3668 | 0.9470   |
| 0.1696        | 2.0   | 1358 | 0.1520          | 0.4094    | 0.5108 | 0.4545 | 0.9532   |
| 0.0952        | 3.0   | 2037 | 0.1455          | 0.4466    | 0.5476 | 0.4920 | 0.9579   |


### Framework versions

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