---
license: mit
base_model: microsoft/biogpt
tags:
- generated_from_trainer
model-index:
- name: biogpt-ner
  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-ner

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: 0.1892
- Overall Precision: 0.4664
- Overall Recall: 0.5553
- Overall F1: 0.5070
- Overall Accuracy: 0.9572

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|
| 0.2307        | 1.0   | 1358 | 0.1703          | 0.3849            | 0.3888         | 0.3869     | 0.9497           |
| 0.1415        | 2.0   | 2716 | 0.1589          | 0.3761            | 0.5286         | 0.4395     | 0.9490           |
| 0.0932        | 3.0   | 4074 | 0.1515          | 0.4580            | 0.5197         | 0.4869     | 0.9560           |
| 0.0763        | 4.0   | 5432 | 0.1763          | 0.4885            | 0.5146         | 0.5012     | 0.9583           |
| 0.0586        | 5.0   | 6790 | 0.1892          | 0.4664            | 0.5553         | 0.5070     | 0.9572           |


### Framework versions

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