---
base_model: gpt2
library_name: transformers
license: mit
metrics:
- accuracy
- f1
- precision
- recall
tags:
- generated_from_trainer
model-index:
- name: results
  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. -->

# results

This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4220
- Accuracy: 0.9117
- F1: 0.9138
- Precision: 0.9087
- Recall: 0.9189

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.2113        | 1.0   | 4210  | 0.5260          | 0.8991   | 0.8991 | 0.9159    | 0.8829 |
| 0.1357        | 2.0   | 8420  | 0.3950          | 0.8968   | 0.9011 | 0.8798    | 0.9234 |
| 0.0988        | 3.0   | 12630 | 0.4220          | 0.9117   | 0.9138 | 0.9087    | 0.9189 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1