roberta-base-CoLA
| Property | Value |
|---|---|
| Base Architecture | RoBERTa |
| Task | Linguistic Acceptability |
| Best Accuracy | 85.04% |
| Model Hub | Hugging Face |
What is roberta-base-CoLA?
roberta-base-CoLA is a specialized variant of the RoBERTa base model, fine-tuned specifically for the Corpus of Linguistic Acceptability (CoLA) task. This model is designed to assess the grammatical acceptability of English sentences, making it valuable for linguistic analysis and natural language processing applications.
Implementation Details
The model was fine-tuned using TextAttack's framework with careful optimization parameters. The training process involved 5 epochs with a batch size of 32, utilizing a learning rate of 2e-05 and a maximum sequence length of 128 tokens. The training employed a cross-entropy loss function, which is standard for classification tasks.
- Training Duration: 5 epochs
- Batch Size: 32
- Learning Rate: 2e-05
- Max Sequence Length: 128
- Best Performance: 85.04% accuracy (achieved after 1 epoch)
Core Capabilities
- Grammatical acceptability judgment
- Binary classification of sentence correctness
- Linguistic pattern recognition
- Sentence structure analysis
Frequently Asked Questions
Q: What makes this model unique?
This model combines RoBERTa's robust language understanding capabilities with specific optimization for linguistic acceptability tasks, achieving high accuracy (85.04%) in determining grammatical correctness.
Q: What are the recommended use cases?
The model is ideal for applications requiring grammatical assessment, including: automated writing evaluation, educational tools, content quality checking, and linguistic research.
