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nostalgic_not_nostalgic_multi_language_ver
vy-wang/nostalgic_not_nostalgic_multi_language_ver
nostalgic_not_nostalgic_multi_language_ver is a text classification model from vy-wang. 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
- Jul 5, 2026
- Updated
- Jul 7, 2026
- SHA
- e2a85134
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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. -->
learn_hf_nostalgic_not_nostalgic_text_classifier-distilbert-base-uncased
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: 0.0934
- Accuracy: 0.97
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: 32
- eval_batch_size: 32
- 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: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6965 | 1.0 | 25 | 0.4732 | 0.88 |
| 0.3605 | 2.0 | 50 | 0.1999 | 0.94 |
| 0.1718 | 3.0 | 75 | 0.0934 | 0.97 |
Framework versions
- Transformers 5.12.1
- Pytorch 2.11.0+cpu
- Datasets 4.0.0
- Tokenizers 0.22.2
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Jul 5, 2026
- Updated
- Jul 7, 2026