metadata
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language: en license: cc-by-4.0 tags:
- text-classification repo: https://huggingface.co./awashh/RoBERTa-NLI-Group71
Model Card for j34330vk-q26752aa-NLI
This is a Natural Language Inference (NLI) classification model that was trained to detect if a hypothesis is true based on a premise.
Model Details
Model Description
This model is based upon a RoBERTa model that was fine-tuned on 26.9K pairs of premise-hypothesis texts.
- Developed by: Awab Alshami and Vansh Kharbanda
- Language(s): English
- Model type: Supervised
- Model architecture: Transformers
- Finetuned from model [optional]: roberta-base
Model Resources
- Repository: https://huggingface.co./FacebookAI/roberta-base
- Paper or documentation: https://arxiv.org/pdf/1907.11692.pdf
Training Details
Training Data
26.9k pairs of premise-hypothesis texts.
Training Procedure
Training Hyperparameters
- learning_rate: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- num_epochs: 8
Speeds, Sizes, Times
- overall training time: 1.2 hours
- duration per training epoch: 9 minutes
- model size: 600 MB
Evaluation
Testing Data & Metrics
Testing Data
A subset of the development set provided, amounting to 6.7K pairs.
Metrics
- Precision: 0.882
- Recall: 0.879
- F1-score: 0.880
- Accuracy: 0.880
Results
The model obtained a precision score of 88.2%, a recall score of 87.9%, an F1-score of 88% and an accuracy of 88%.
Technical Specifications
Hardware
- RAM: at least 22.5 GB
- Storage: at least 2GB,
- GPU: A100
Software
- Transformers 4.18.0
- Pytorch 1.11.0+cu113
Bias, Risks, and Limitations
Any inputs (concatenation of two sequences) longer than 512 subwords will be truncated by the model.