---
library_name: peft
license: mit
base_model: gpt2
tags:
- generated_from_trainer
datasets:
- hatexplain
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: finetuned-gpt2-lora-hatexplain
  results: []
---

<!-- 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. -->

# finetuned-gpt2-lora-hatexplain

This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the hatexplain dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7617
- Accuracy: 0.6954
- Precision: 0.6905
- Recall: 0.6954
- F1: 0.6911

## 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: 0.0005
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.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: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.6763        | 1.0   | 1923 | 0.7699          | 0.6629   | 0.6552    | 0.6629 | 0.6429 |
| 0.8192        | 2.0   | 3846 | 0.7648          | 0.6712   | 0.6620    | 0.6712 | 0.6628 |
| 0.7806        | 3.0   | 5769 | 0.7657          | 0.6571   | 0.6682    | 0.6571 | 0.6585 |
| 0.6273        | 4.0   | 7692 | 0.8046          | 0.6769   | 0.6727    | 0.6769 | 0.6740 |


### Framework versions

- PEFT 0.14.0
- Transformers 4.47.0
- Pytorch 2.5.1+cu118
- Datasets 3.1.0
- Tokenizers 0.21.0