Upload README.md with huggingface_hub

README.md

@@ -0,0 +1,41 @@
+---
+language: en
+tags:
+- sentiment-analysis
+- flan-t5
+- text-classification
+license: apache-2.0
+datasets:
+- imdb
+---
+
+# FLAN-T5 Small - Sentiment Analysis
+
+Fine-tuned version of `google/flan-t5-small` for sentiment analysis on IMDB reviews.
+
+## Model Details
+- **Base Model:** google/flan-t5-small
+- **Task:** Binary sentiment classification (positive/negative)
+- **Dataset:** IMDB movie reviews (300 training samples)
+- **Accuracy:** 85.00%
+
+## Usage
+
+```python
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+tokenizer = AutoTokenizer.from_pretrained("usef310/flan-t5-small-sentiment")
+model = AutoModelForSeq2SeqLM.from_pretrained("usef310/flan-t5-small-sentiment")
+
+text = "This movie was amazing!"
+inputs = tokenizer("sentiment: " + text, return_tensors="pt")
+outputs = model.generate(**inputs)
+prediction = tokenizer.decode(outputs[0], skip_special_tokens=True)
+print(prediction)  # Output: positive or negative
+```
+
+## Training Details
+- Epochs: 3
+- Batch size: 4 (with gradient accumulation)
+- Learning rate: 5e-5
+- Optimizer: AdamW