peft safetensors parquet text-classification dataset:ag_news base_model:korca/bae-roberta-base-boolq base_model:adapter:korca/bae-roberta-base-boolq model-index region:us
---
base_model: korca/bae-roberta-base-boolq
datasets:
- ag_news
library_name: peft
metrics:
- accuracy
tags:
- parquet
- text-classification
model-index:
- name: korca_bae-roberta-base-boolq-finetuned-lora-ag_news
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: ag_news
      type: ag_news
      config: default
      split: test
      args: default
    metrics:
    - type: accuracy
      value: 0.9393421052631579
      name: accuracy
---

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# korca_bae-roberta-base-boolq-finetuned-lora-ag_news

This model is a fine-tuned version of [korca/bae-roberta-base-boolq](https://huggingface.co/korca/bae-roberta-base-boolq) on the ag_news dataset.
It achieves the following results on the evaluation set:
- accuracy: 0.9393

## 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: 0.0004
- train_batch_size: 24
- eval_batch_size: 24
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| accuracy | train_loss | epoch |
|:--------:|:----------:|:-----:|
| 0.3011   | None       | 0     |
| 0.9221   | 0.2875     | 0     |
| 0.9267   | 0.2262     | 1     |
| 0.9380   | 0.2007     | 2     |
| 0.9393   | 0.1873     | 3     |


### Framework versions

- PEFT 0.8.2
- Transformers 4.37.2
- Pytorch 2.2.0
- Datasets 2.16.1
- Tokenizers 0.15.2