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TRAIN_SET-xlm-roberta-base-vianli-h
dtran612/TRAIN_SET-xlm-roberta-base-vianli-h
TRAIN_SET-xlm-roberta-base-vianli-h is a text classification model from dtran612. 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
- xlm-roberta
- Access
- Public
- Created
- May 7, 2026
- Updated
- May 7, 2026
- SHA
- f70611e5
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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. -->
TRAIN_SET-xlm-roberta-base-vianli-h
This model is a fine-tuned version of xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.1619
- Accuracy: 0.386
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: 16
- eval_batch_size: 8
- 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: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.0795 | 1.0 | 501 | 1.1493 | 0.33 |
| 1.0700 | 2.0 | 1002 | 1.1035 | 0.359 |
| 1.0469 | 3.0 | 1503 | 1.1089 | 0.38 |
| 0.9730 | 4.0 | 2004 | 1.1619 | 0.386 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- May 7, 2026
- Updated
- May 7, 2026