metadata
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
distilgpt2-finetuned-python_code_instructions_18k_alpaca
This model is a fine-tuned version of 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