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# Model Card for t5_small Summarization Model

## Model Details
This model is a t5-small for studing Text Summarization.

## Training Data
The model was trained on the cnn_dailymail dataset.

## Training Procedure
- **Learning Rate** : 2e-5 
- **Epochs** : 5
- **Batch Size ** : 4

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

tokenizer = AutoTokenizer.from_pretrained("t5-small")
model = AutoModelForSequenceClassification.from_pretrained("t5-small")

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

## Evaluation
- **Accuracy** : i don't know well.
## 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.