language:
- en
license: wtfpl
library_name: transformers
tags:
- code
- text-generation-inference
datasets:
- flytech/python-codes-25k
- espejelomar/code_search_net_python_10000_examples
metrics:
- accuracy
pipeline_tag: text-generation
Model Card for GPT_2_CODE
-Goal is to create a small GPT2 python coder
Table of Contents
- Model Card for GPT_2_CODE
- Table of Contents
- Table of Contents
- Model Details
- Uses
- Bias, Risks, and Limitations
- Training Details
- Evaluation
- Model Examination
- Environmental Impact
- Technical Specifications [optional]
- Citation
- Glossary [optional]
- More Information [optional]
- Model Card Authors [optional]
- Model Card Contact
- How to Get Started with the Model
Model Details
Model Description
WIP,Goal is to create a small GPT2 python coder
- Developed by: C, o, d, e, M, o, n, k, e, y
- Shared by [Optional]: More information needed
- Model type: Language model
- Language(s) (NLP): eng
- License: wtfpl
- Parent Model: More information needed
- Resources for more information: More information needed
Uses
coding assistant
Direct Use
generate python code snippets
Downstream Use [Optional]
semi auto coder
Out-of-Scope Use
describe code Keep Finetuning on question/python datasets
Training Details
Training Data
flytech/python-codes-25k espejelomar/code_search_net_python_10000_examples
Training Procedure
Train/Val/Scheduler
Preprocessing
More information needed
Speeds, Sizes, Times
Epochs 3
"flytech/python-codes-25k"
Training Loss: 0.4007 Validation Loss: 0.5526 Epochs 3
"espejelomar/code_search_net_python_10000_examples"
--Starting Loss: 2.0862 -Epoch 1/4 | Training Loss: 1.5355 | Validation Loss: 1.1723 -Epoch 2/4 | Training Loss: 1.0501 | Validation Loss: 1.0702 -Epoch 3/4 | Training Loss: 0.9804 | Validation Loss: 1.0798 -Epoch 4/4 | Training Loss: 0.9073 | Validation Loss: 1.0772
Evaluation
Manual comparison with base model
Testing Data
flytech/python-codes-25k espejelomar/code_search_net_python_10000_examples
Factors
80/20 train/val
Metrics
train/validate lr scheduling
Results
Better in python code generation as base gpt2-medium model
Model Examination
More information needed
Environmental Impact
- Hardware Type: CPU and Colab T4
- Hours used: 4
- Cloud Provider: Google Colab
- Compute Region: NL
Model Architecture and Objective
gpt2
Compute Infrastructure
More information needed
Hardware
CPU and Colab T4
Software
pytorch, custom python
More Information [optional]
Experimental
Model Card Authors [optional]
CodeMonkeyXL
Model Card Contact
K00B404 huggingface
How to Get Started with the Model
Use the code below to get started with the model.