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roberta-large-finetuned-vihallu-nli
sercetexam9/roberta-large-finetuned-vihallu-nli
roberta-large-finetuned-vihallu-nli is a text classification model from sercetexam9. 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
- Oct 1, 2025
- Updated
- Oct 1, 2025
- SHA
- d074bc2d
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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. -->
roberta-large-finetuned-vihallu-nli
This model is a fine-tuned version of ynie/roberta-large-snli_mnli_fever_anli_R1_R2_R3-nli on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6911
- Accuracy: 0.7935
- F1 Macro: 0.7932
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 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_ratio: 0.1
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro |
|---|---|---|---|---|---|
| 0.6176 | 1.0 | 430 | 0.6467 | 0.7869 | 0.7871 |
| 0.4068 | 2.0 | 860 | 0.6911 | 0.7935 | 0.7932 |
Framework versions
- Transformers 4.56.2
- Pytorch 2.6.0+cu124
- Datasets 4.1.1
- Tokenizers 0.22.1
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Oct 1, 2025
- Updated
- Oct 1, 2025