---
license: apache-2.0
datasets:
- ambrosfitz/cnn-daily-grammar
language:
- en
base_model:
- google-t5/t5-base
pipeline_tag: summarization
---
# T5-CNN-Grammar-Enhanced

## Model Description
A T5-base model fine-tuned on the CNN Daily Grammar dataset for enhanced summarization with grammatical structure awareness.

## Usage
```python
from transformers import AutoTokenizer, AutoModelForSeq2SeqGeneration

tokenizer = AutoTokenizer.from_pretrained("username/t5-cnn-grammar-enhanced")
model = AutoModelForSeq2SeqGeneration.from_pretrained("username/t5-cnn-grammar-enhanced")
```

## Training Details
- Base model: t5-base
- Dataset: CNN Daily Grammar
- Training type: Fine-tuning
- Framework: PyTorch
- Epochs: 10
- Batch size: 8
- Learning rate: 2e-5
- Loss: Focal Loss
- Scheduler: Linear warmup
- Best validation loss: 0.7759

## Model Architecture
- Encoder-decoder transformer
- Grammar-enhanced input structure
- Focal loss for detail retention

## Evaluation Results
Final validation metrics:
- Loss: 0.7759
- Strong performance on detail retention and factual accuracy

## Limitations
- Limited to news article summarization
- May omit specific numerical details
- Best suited for formal news content

## License
Apache 2.0