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output-roberta
tmarkspengler/output-roberta
output-roberta is a text classification model from tmarkspengler. Use it when you need a label for a piece of text. 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
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- roberta
- Access
- Public
- Created
- Dec 12, 2025
- Updated
- Dec 12, 2025
- SHA
- aa62bc34
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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. -->
output-roberta
This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0339
- Accuracy: 0.9951
- F1 Macro: 0.9948
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro |
|---|---|---|---|---|---|
| 0.0863 | 1.0 | 1255 | 0.0317 | 0.9910 | 0.9906 |
| 0.0336 | 2.0 | 2510 | 0.0303 | 0.9928 | 0.9925 |
| 0.0135 | 3.0 | 3765 | 0.0339 | 0.9951 | 0.9948 |
Framework versions
- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.4.1
- Tokenizers 0.22.1
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Dec 12, 2025
- Updated
- Dec 12, 2025