# Model Card for t5_small Summarization Model

## Model Details
This model is a fine-tuned version of t5_small on the CNN/Daily Mail dataset
for summarization tasks.

## Training Data
The model was trained on the CNN/Daily Mail dataset.

## Training Procedure
- **Learning Rate**: 5e-5
- **Epochs**: 3
- **Batch Size**: 16

## How to Use
```python
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

tokenizer = AutoTokenizer.from_pretrained("hskang/cnn_dailymail_t5_small")
model = AutoModelForSeq2SeqLM.from_pretrained("hskang/cnn_dailymail_t5_small")

input_text = "upstage tutorial text summarization code"
inputs = tokenizer.encode(input_text, return_tensors="pt")
outputs = model.generate(inputs)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
```

## Evaluation
- **ROUGE-1**: 23.45
- **ROUGE-2**: 7.89
- **ROUGE-L**: 21.34
- **BLEU**: 13.56

## Limitations
The model may generate biased or inappropriate content due to the nature
of the training data.
It is recommended to use the model with caution and apply necessary filters.

## Ethical Considerations
Bias: The model may inherit biases present in the training data.
Misuse: The model can be misused to generate misleading or harmful content.
Copyright and License
This model is licensed under the MIT License.