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---
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
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