---
license: mit
base_model: microsoft/biogpt
tags:
- generated_from_trainer
model-index:
- name: results
  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. -->

# results

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: 0.1870
- Overall Precision: 0.4821
- Overall Recall: 0.5760
- Overall F1: 0.5249
- Overall Accuracy: 0.9506

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|
| 0.2295        | 1.0   | 1358 | 0.1735          | 0.3341            | 0.3926         | 0.3610     | 0.9483           |
| 0.1401        | 2.0   | 2716 | 0.1512          | 0.3905            | 0.5413         | 0.4537     | 0.9509           |
| 0.0948        | 3.0   | 4074 | 0.1627          | 0.4667            | 0.5070         | 0.4860     | 0.9578           |
| 0.0778        | 4.0   | 5432 | 0.1672          | 0.4831            | 0.5642         | 0.5205     | 0.9587           |
| 0.0614        | 5.0   | 6790 | 0.1755          | 0.4967            | 0.5781         | 0.5344     | 0.9594           |


### Framework versions

- Transformers 4.39.3
- Pytorch 1.12.1+cu113
- Datasets 2.18.0
- Tokenizers 0.15.2