---
license: mit
tags:
- generated_from_trainer
datasets:
- ncbi_disease
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BIO_GPT_NER_FINETUNED_C
  results:
  - task:
      name: Token Classification
      type: token-classification
    dataset:
      name: ncbi_disease
      type: ncbi_disease
      config: ncbi_disease
      split: validation
      args: ncbi_disease
    metrics:
    - name: Precision
      type: precision
      value: 0.44176706827309237
    - name: Recall
      type: recall
      value: 0.5583756345177665
    - name: F1
      type: f1
      value: 0.4932735426008968
    - name: Accuracy
      type: accuracy
      value: 0.958054734877935
---

<!-- 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. -->

# BIO_GPT_NER_FINETUNED_C

This model is a fine-tuned version of [microsoft/biogpt](https://huggingface.co/microsoft/biogpt) on the ncbi_disease dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1466
- Precision: 0.4418
- Recall: 0.5584
- F1: 0.4933
- Accuracy: 0.9581

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2989        | 1.0   | 680  | 0.1687          | 0.3350    | 0.4226 | 0.3737 | 0.9474   |
| 0.1764        | 2.0   | 1360 | 0.1425          | 0.4289    | 0.5241 | 0.4717 | 0.9560   |
| 0.0942        | 3.0   | 2040 | 0.1466          | 0.4418    | 0.5584 | 0.4933 | 0.9581   |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3