Bert Base Uncased Sst2 Distilled
This model is a fine-tuned version of bert-base-uncased on an unknown dataset, primarily used for text classification tasks.
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Release Time : 3/2/2022
Model Overview
This is a distilled BERT model based on the bert-base-uncased architecture, fine-tuned on the SST-2 (Stanford Sentiment Treebank) dataset for sentiment analysis tasks.
Model Features
Distilled Model
Learns from a larger teacher model through knowledge distillation, reducing model size while maintaining performance.
High Accuracy
Achieves an accuracy of 90.25% on the evaluation set, demonstrating excellent performance.
Efficient Fine-tuning
Fine-tuned based on the pre-trained bert-base-uncased model, ensuring high training efficiency.
Model Capabilities
Text Classification
Sentiment Analysis
Natural Language Understanding
Use Cases
Sentiment Analysis
Product Review Sentiment Classification
Analyze whether user reviews of a product are positive or negative.
Accuracy reaches 90.25%
Social Media Sentiment Monitoring
Monitor the emotional tendencies of users on social media regarding specific topics.
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