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xlmr-vi-nli
lyle49/xlmr-vi-nli
xlmr-vi-nli is a machine learning model from lyle49. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- License
- mit
- Model type
- xlm-roberta
- Access
- Public
- Created
- Sep 14, 2025
- Updated
- Oct 12, 2025
- SHA
- 5c243bf0
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. -->
xlmr-vi-nli
This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2354
- Accuracy: 0.9796
- F1 Macro: 0.9796
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: 8
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro |
|---|---|---|---|---|---|
| 0.2665 | 0.9994 | 882 | 0.2531 | 0.9745 | 0.9745 |
| 0.2312 | 2.0 | 1765 | 0.2445 | 0.9756 | 0.9756 |
| 0.1965 | 2.9994 | 2647 | 0.2278 | 0.9807 | 0.9808 |
| 0.1829 | 3.9977 | 3528 | 0.2312 | 0.9807 | 0.9807 |
Framework versions
- Transformers 4.43.3
- Pytorch 2.6.0+cu124
- Datasets 2.21.0
- Tokenizers 0.19.1
- Type
- xlm-roberta
- License
- mit
- Created
- Sep 14, 2025
- Updated
- Oct 12, 2025