---
license: mit
base_model: gpt2
tags:
- text-generation
- generated_from_trainer
model-index:
- name: gpt2-small-finetuned-codeparrot-ds_nlp-course-chapter7-section5
  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-small-finetuned-codeparrot-ds_nlp-course-chapter7-section5

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: 1.0606

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 2.5691        | 0.08  | 5000  | 1.7463          |
| 1.6818        | 0.15  | 10000 | 1.5248          |
| 1.5328        | 0.23  | 15000 | 1.4226          |
| 1.4521        | 0.31  | 20000 | 1.3569          |
| 1.3944        | 0.38  | 25000 | 1.3030          |
| 1.3422        | 0.46  | 30000 | 1.2558          |
| 1.2976        | 0.54  | 35000 | 1.2129          |
| 1.2514        | 0.61  | 40000 | 1.1714          |
| 1.2089        | 0.69  | 45000 | 1.1321          |
| 1.1737        | 0.77  | 50000 | 1.0990          |
| 1.1427        | 0.84  | 55000 | 1.0758          |
| 1.1242        | 0.92  | 60000 | 1.0636          |
| 1.1142        | 1.0   | 65000 | 1.0606          |


### Framework versions

- Transformers 4.35.2
- Pytorch 1.11.0+cu102
- Datasets 2.15.0
- Tokenizers 0.15.0