---
license: mit
tags:
- generated_from_trainer
metrics:
- bleu
base_model: openai-community/gpt2
model-index:
- name: gpt2-finetuned
  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-finetuned

This model is a fine-tuned version of [openai-community/gpt2](https://huggingface.co/openai-community/gpt2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6944
- Bleu: 0.0294
- Bertscore Precision: 0.1536
- Bertscore Recall: 0.1658
- Bertscore F1: 0.1592

## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Bleu   | Bertscore Precision | Bertscore Recall | Bertscore F1 |
|:-------------:|:-----:|:------:|:---------------:|:------:|:-------------------:|:----------------:|:------------:|
| 4.716         | 1.0   | 5750   | 3.4413          | 0.0112 | 0.1417              | 0.1575           | 0.1489       |
| 4.5916        | 2.0   | 11500  | 3.2372          | 0.0119 | 0.1424              | 0.1583           | 0.1496       |
| 4.325         | 3.0   | 17250  | 3.0534          | 0.0128 | 0.1430              | 0.1587           | 0.1501       |
| 4.1626        | 4.0   | 23000  | 2.9061          | 0.0136 | 0.1433              | 0.1592           | 0.1505       |
| 4.0255        | 5.0   | 28750  | 2.7554          | 0.0148 | 0.1438              | 0.1599           | 0.1511       |
| 3.862         | 6.0   | 34500  | 2.6185          | 0.0346 | 0.1446              | 0.1605           | 0.1518       |
| 3.7367        | 7.0   | 40250  | 2.4945          | 0.0286 | 0.1456              | 0.1611           | 0.1527       |
| 3.7907        | 8.0   | 46000  | 2.3799          | 0.0401 | 0.1488              | 0.1617           | 0.1548       |
| 3.5181        | 9.0   | 51750  | 2.2704          | 0.0607 | 0.1490              | 0.1623           | 0.1551       |
| 3.3377        | 10.0  | 57500  | 2.1710          | 0.0804 | 0.1498              | 0.1627           | 0.1558       |
| 3.294         | 11.0  | 63250  | 2.0876          | 0.0221 | 0.1512              | 0.1633           | 0.1568       |
| 3.1612        | 12.0  | 69000  | 2.0004          | 0.0234 | 0.1516              | 0.1637           | 0.1572       |
| 3.1257        | 13.0  | 74750  | 1.9356          | 0.0244 | 0.1518              | 0.1642           | 0.1575       |
| 3.1347        | 14.0  | 80500  | 1.8769          | 0.0257 | 0.1525              | 0.1646           | 0.1581       |
| 2.8094        | 15.0  | 86250  | 1.8210          | 0.0268 | 0.1527              | 0.1649           | 0.1584       |
| 2.8519        | 16.0  | 92000  | 1.7776          | 0.0275 | 0.1530              | 0.1652           | 0.1587       |
| 2.782         | 17.0  | 97750  | 1.7438          | 0.0282 | 0.1532              | 0.1654           | 0.1589       |
| 2.9097        | 18.0  | 103500 | 1.7183          | 0.0289 | 0.1535              | 0.1657           | 0.1591       |
| 2.881         | 19.0  | 109250 | 1.6999          | 0.0293 | 0.1536              | 0.1658           | 0.1592       |
| 2.6302        | 20.0  | 115000 | 1.6944          | 0.0294 | 0.1536              | 0.1658           | 0.1592       |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1