---
license: mit
tags:
- generated_from_trainer
metrics:
- f1
- recall
- accuracy
model-index:
- name: GPT2-THESIS
  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-THESIS

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: 0.9762
- F1: 0.7492
- Recall: 0.7492
- Accuracy: 0.7492

## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | F1     | Recall | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:--------:|
| 1.1822        | 1.0   | 1446  | 0.9362          | 0.7065 | 0.7065 | 0.7065   |
| 0.8791        | 2.0   | 2892  | 0.8616          | 0.7303 | 0.7303 | 0.7303   |
| 0.7218        | 3.0   | 4338  | 0.8250          | 0.7406 | 0.7406 | 0.7406   |
| 0.6025        | 4.0   | 5784  | 0.8351          | 0.7509 | 0.7509 | 0.7509   |
| 0.5142        | 5.0   | 7230  | 0.8781          | 0.7477 | 0.7477 | 0.7477   |
| 0.453         | 6.0   | 8676  | 0.8871          | 0.7526 | 0.7526 | 0.7526   |
| 0.3813        | 7.0   | 10122 | 0.9216          | 0.7475 | 0.7475 | 0.7475   |
| 0.3399        | 8.0   | 11568 | 0.9458          | 0.7477 | 0.7477 | 0.7477   |
| 0.3049        | 9.0   | 13014 | 0.9650          | 0.7504 | 0.7504 | 0.7504   |
| 0.2861        | 10.0  | 14460 | 0.9762          | 0.7492 | 0.7492 | 0.7492   |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3