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CSQA_roberta_large
gulsmyigit/CSQA_roberta_large
CSQA_roberta_large is a multiple choice model from gulsmyigit. Use it for the multiple choice task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- multiple choice
- Library
- transformers
- License
- mit
- Model type
- roberta
- Access
- Public
- Created
- May 5, 2025
- Updated
- May 5, 2025
- SHA
- d2153673
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
test-glue
This model is a fine-tuned version of FacebookAI/roberta-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6847
- Accuracy: 0.7232
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.98) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 150
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.9984 | 304 | 0.9992 | 0.6224 |
| 1.352 | 1.9984 | 608 | 0.7015 | 0.7150 |
| 1.352 | 2.9984 | 912 | 0.6847 | 0.7232 |
Framework versions
- Transformers 4.52.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 3.5.2.dev0
- Tokenizers 0.21.1
- Task
- multiple choice
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- May 5, 2025
- Updated
- May 5, 2025