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

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: 0.0776
- Precision: 0.6554
- Recall: 0.7769
- F1: 0.7110
- Accuracy: 0.9720

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2614        | 1.0   | 665  | 0.1613          | 0.6132    | 0.4708 | 0.5326 | 0.9406   |
| 0.1694        | 2.0   | 1330 | 0.0951          | 0.5704    | 0.7198 | 0.6365 | 0.9654   |
| 0.1298        | 3.0   | 1995 | 0.0776          | 0.6554    | 0.7769 | 0.7110 | 0.9720   |


### Framework versions

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