AnkitAI/reviews-roberta-base-sentiment-analysis

🌟 Fine-tuned RoBERTa for Sentiment Analysis on Reviews 🌟

This is a fine-tuned version of cardiffnlp/twitter-roberta-base-sentiment-latest on the Amazon Reviews dataset for sentiment analysis.

📜 Model Details

• 🆕 Model Name: AnkitAI/reviews-roberta-base-sentiment-analysis
• 🔗 Base Model: cardiffnlp/twitter-roberta-base-sentiment-latest
• 📊 Dataset: Amazon Reviews
• ⚙️ 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
• ⚖️ Weight Decay: 0.01
• 📅 Evaluation Strategy: Epoch

🏋️ Training Details

• 📉 Eval Loss: 0.1049
• ⏱️ Eval Runtime: 3177.538 seconds
• 📈 Eval Samples/Second: 226.591
• 🌀 Eval Steps/Second: 7.081
• 🏃 Train Runtime: 110070.6349 seconds
• 📊 Train Samples/Second: 78.495
• 🌀 Train Steps/Second: 2.453
• 📉 Train Loss: 0.0858
• ⏳ Eval Accuracy: 97.19%
• 🌀 Eval Precision: 97.9%
• ⏱️ Eval Recall: 97.18%
• 📈 Eval F1 Score: 97.19%

🚀 Usage

You can use this model directly with the Hugging Face transformers library:

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) # 1 for positive, 0 for negative

📜 License

This model is licensed under the MIT License.