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model_question_answering
davidsilva824/model_question_answering
model_question_answering is a text classification model from davidsilva824. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- roberta
- Access
- Public
- Created
- Jun 2, 2025
- Updated
- Jun 2, 2025
- SHA
- 7773e6c9
Try a prompt
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. -->
model_question_answering
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5438
- Accuracy: 0.7936
- F1: 0.7926
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: 4e-05
- train_batch_size: 12
- eval_batch_size: 12
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 96
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 20
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.4542 | 0.4071 | 40 | 0.5258 | 0.7599 | 0.7433 |
| 0.3783 | 0.8142 | 80 | 0.5738 | 0.7685 | 0.7707 |
| 0.2734 | 1.2137 | 120 | 0.6156 | 0.7823 | 0.7818 |
| 0.216 | 1.6209 | 160 | 0.5846 | 0.7945 | 0.7916 |
Framework versions
- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- Created
- Jun 2, 2025
- Updated
- Jun 2, 2025