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---
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