---
license: mit
tags:
- generated_from_trainer
datasets:
- ncbi_disease
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BIO_GPT_NER_FINETUNED_NEW_2
  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: 0.10112359550561797
    - name: Recall
      type: recall
      value: 0.10279187817258884
    - name: F1
      type: f1
      value: 0.10195091252359975
    - name: Accuracy
      type: accuracy
      value: 0.9362074327476286
---

<!-- 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_NEW_2

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: 0.2186
- Precision: 0.1011
- Recall: 0.1028
- F1: 0.1020
- Accuracy: 0.9362

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.3345        | 1.0   | 680  | 0.2445          | 0.0119    | 0.0063 | 0.0083 | 0.9302   |
| 0.2491        | 2.0   | 1360 | 0.2199          | 0.0813    | 0.0888 | 0.0849 | 0.9320   |
| 0.1823        | 3.0   | 2040 | 0.2186          | 0.1011    | 0.1028 | 0.1020 | 0.9362   |


### Framework versions

- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3