---
library_name: transformers
license: mit
base_model: microsoft/biogpt
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: TAC_dataset
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# TAC_dataset

This model is a fine-tuned version of [microsoft/biogpt](https://huggingface.co/microsoft/biogpt) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3005
- Precision: 0.125
- Recall: 0.0018
- F1: 0.0036
- Accuracy: 0.9191

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3

### Training results



### Framework versions

- Transformers 4.51.2
- Pytorch 2.1.0+cu121
- Datasets 3.5.0
- Tokenizers 0.21.1