# Model Card for t5_small Summarization Model

## Model Details
This model is a fine-tuned version of T5-small-base for summarization.

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

## Training Procedure
- **Epochs**: 1

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

tokenizer = AutoTokenizer.from_pretrained("summarization")
model = AutoModelForSeq2SeqLM.from_pretrained("summarization")

input_text = "The movie was fantastic with a gripping storyline!"
inputs = tokenizer.encode(input_text, return_tensors="pt")
outputs = model(inputs)
```

## Evaluation
- **BLEU-4**: 42.86

## 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.