---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- recall
- precision
model-index:
- name: gpt2_human
  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. -->

# gpt2_human

This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4323
- Accuracy: {'accuracy': 0.8127125850340136}
- F1: 0.8108
- Recall: 0.7227
- Precision: 0.8380

## 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: 0.001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy                         | F1     | Recall | Precision |
|:-------------:|:-----:|:-----:|:---------------:|:--------------------------------:|:------:|:------:|:---------:|
| 0.8137        | 1.0   | 10976 | 0.6581          | {'accuracy': 0.6217049319727891} | 0.6205 | 0.5507 | 0.5835    |
| 0.4538        | 2.0   | 21952 | 0.4323          | {'accuracy': 0.8127125850340136} | 0.8108 | 0.7227 | 0.8380    |


### Framework versions

- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3