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TRAIN_SET-xlm-roberta-base-vinli-h
dtran612/TRAIN_SET-xlm-roberta-base-vinli-h
TRAIN_SET-xlm-roberta-base-vinli-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
- 759d5b71
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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-vinli-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: 1.0404
- Accuracy: 0.5442
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 |
|---|---|---|---|---|
| 1.0523 | 1.0 | 1143 | 1.0205 | 0.4841 |
| 0.9306 | 2.0 | 2286 | 0.9800 | 0.5367 |
| 0.8924 | 3.0 | 3429 | 1.0066 | 0.5358 |
| 0.7116 | 4.0 | 4572 | 1.0404 | 0.5442 |
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