---
library_name: transformers
license: mit
base_model: gpt2
tags:
- generated_from_trainer
model-index:
- name: codeparrot-ds-small
  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. -->

# codeparrot-ds-small

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: 3.2919

## Model description

Due to hardware limitations and an insufficient amount of training data, 
the model has only been trained for a single epoch and is currently not functional.

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 5.9286        | 0.02  | 500   | 5.7197          |
| 5.2717        | 0.04  | 1000  | 5.1488          |
| 4.9972        | 0.06  | 1500  | 4.8345          |
| 4.8214        | 0.08  | 2000  | 4.6251          |
| 4.6272        | 0.1   | 2500  | 4.4807          |
| 4.5241        | 0.12  | 3000  | 4.3484          |
| 4.405         | 0.14  | 3500  | 4.2483          |
| 4.3189        | 0.16  | 4000  | 4.1680          |
| 4.2596        | 0.18  | 4500  | 4.0914          |
| 4.2569        | 0.2   | 5000  | 4.0341          |
| 4.1614        | 0.22  | 5500  | 3.9615          |
| 4.1073        | 0.24  | 6000  | 3.9112          |
| 4.0892        | 0.26  | 6500  | 3.8685          |
| 4.0151        | 0.28  | 7000  | 3.8277          |
| 3.903         | 0.3   | 7500  | 3.7787          |
| 3.9248        | 0.32  | 8000  | 3.7447          |
| 3.8978        | 0.34  | 8500  | 3.7189          |
| 3.9231        | 0.36  | 9000  | 3.6877          |
| 3.8936        | 0.38  | 9500  | 3.6479          |
| 3.7649        | 0.4   | 10000 | 3.6154          |
| 3.8156        | 0.42  | 10500 | 3.6069          |
| 3.7588        | 0.44  | 11000 | 3.5772          |
| 3.7559        | 0.46  | 11500 | 3.5517          |
| 3.814         | 0.48  | 12000 | 3.5230          |
| 3.7384        | 0.5   | 12500 | 3.5065          |
| 3.6827        | 0.52  | 13000 | 3.4807          |
| 3.6679        | 0.54  | 13500 | 3.4585          |
| 3.6838        | 0.56  | 14000 | 3.4419          |
| 3.7154        | 0.58  | 14500 | 3.4313          |
| 3.7117        | 0.6   | 15000 | 3.4156          |
| 3.6065        | 0.62  | 15500 | 3.3990          |
| 3.613         | 0.64  | 16000 | 3.3820          |
| 3.5824        | 0.66  | 16500 | 3.3702          |
| 3.6263        | 0.68  | 17000 | 3.3645          |
| 3.6073        | 0.7   | 17500 | 3.3529          |
| 3.587         | 0.72  | 18000 | 3.3419          |
| 3.624         | 0.74  | 18500 | 3.3340          |
| 3.583         | 0.76  | 19000 | 3.3273          |
| 3.573         | 0.78  | 19500 | 3.3185          |
| 3.5576        | 0.8   | 20000 | 3.3123          |
| 3.5623        | 0.82  | 20500 | 3.3103          |
| 3.5955        | 0.84  | 21000 | 3.3053          |
| 3.5947        | 0.86  | 21500 | 3.3015          |
| 3.5258        | 0.88  | 22000 | 3.2989          |
| 3.5985        | 0.9   | 22500 | 3.2962          |
| 3.5723        | 0.92  | 23000 | 3.2938          |
| 3.5863        | 0.94  | 23500 | 3.2927          |
| 3.5378        | 0.96  | 24000 | 3.2921          |
| 3.4952        | 0.98  | 24500 | 3.2919          |
| 3.5357        | 1.0   | 25000 | 3.2919          |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.5.1
- Datasets 2.19.1
- Tokenizers 0.21.1