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---
tags:
- autotrain
- summarization
language:
- en
widget:
- text: >
def preprocess(text: str) -> str:
text = str(text)
text = text.replace('\\n', ' ')
tokenized_text = text.split(' ')
preprocessed_text = " ".join([token for token in tokenized_text if token])
return preprocessed_text
datasets:
- sagard21/autotrain-data-code-explainer
co2_eq_emissions:
emissions: 5.393079045128973
license: mit
pipeline_tag: summarization
---
# Model Trained Using AutoTrain
- Problem type: Summarization
- Model ID: 2745581349
- CO2 Emissions (in grams): 5.3931
# Model Description
This model is an attempt to simplify code understanding by generating line by line explanation of a source code. This model was fine-tuned using the Salesforce/codet5-large model. Currently it is trained on a small subset of Python snippets.
# Model Usage
```py
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("sagard21/python-code-explainer")
model = AutoModelForSeq2SeqLM.from_pretrained("sagard21/python-code-explainer")
```
## Validation Metrics
- Loss: 2.156
- Rouge1: 29.375
- Rouge2: 18.128
- RougeL: 25.445
- RougeLsum: 28.084
- Gen Len: 19.000
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