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README.md

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-license: mit
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+---
+license: mit
+pipeline_tag: text-classification
+---
+
+# Fine-tuned RoBERTa for Sentiment Analysis on Amazon Reviews
+
+This is a fine-tuned version of [cardiffnlp/twitter-roberta-base-sentiment-latest](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment-latest) on the [Amazon Reviews dataset](https://www.kaggle.com/datasets/bittlingmayer/amazonreviews) for sentiment analysis.
+
+## Model Details
+
+- **Model Name:** AnkitAI/reviews-roberta-base-sentiment-analysis
+- **Base Model:** cardiffnlp/twitter-roberta-base-sentiment-latest
+- **Dataset:** [Amazon Reviews](https://www.kaggle.com/datasets/bittlingmayer/amazonreviews)
+- **Fine-tuning:** This model was fine-tuned for sentiment analysis with a classification head for binary sentiment classification (positive and negative).
+
+## Training
+
+The model was trained using the following parameters:
+
+- **Learning Rate:** 2e-5
+- **Batch Size:** 16
+- **Epochs:** 3
+- **Weight Decay:** 0.01
+- **Evaluation Strategy:** Epoch
+
+## Usage
+
+You can use this model directly with the Hugging Face `transformers` library:
+
+```python
+from transformers import RobertaForSequenceClassification, RobertaTokenizer
+
+model_name = "AnkitAI/reviews-roberta-base-sentiment-analysis"
+model = RobertaForSequenceClassification.from_pretrained(model_name)
+tokenizer = RobertaTokenizer.from_pretrained(model_name)
+
+# Example usage
+inputs = tokenizer("This product is great!", return_tensors="pt")
+outputs = model(**inputs)
+```
+## License
+
+This model is licensed under the mit license