---
license: mit
widget:
- text: My name is Julien and I like to
  example_title: Julien
- text: My name is Merve and my favorite
  example_title: Merve
base_model: distilgpt2
tags:
- generated_from_trainer
- code
model-index:
- name: distilgpt2-finetuned-python_code_instructions_18k_alpaca
  results: []
datasets:
- iamtarun/python_code_instructions_18k_alpaca
language:
- en
metrics:
- accuracy
library_name: transformers
pipeline_tag: text-generation
---

<!-- 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. -->

# distilgpt2-finetuned-python_code_instructions_18k_alpaca

This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5063

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 1.7264        | 1.0   | 3861  | 1.5890          |
| 1.6046        | 2.0   | 7722  | 1.5214          |
| 1.5359        | 3.0   | 11583 | 1.5063          |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2