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---
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 |