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xlmroberta_clir_cross_translation_augmentation_val_kin
shanhy/xlmroberta_clir_cross_translation_augmentation_val_kin
xlmroberta_clir_cross_translation_augmentation_val_kin is a text classification model from shanhy. 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
- Jan 17, 2024
- Updated
- Jan 17, 2024
- SHA
- 36a6f124
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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. -->
xlmroberta_clir_cross_translation_augmentation_val_kin
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: 0.0448
- Spearman Corr: 0.4959
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: 128
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Spearman Corr |
|---|---|---|---|---|
| No log | 1.0 | 412 | 0.0314 | 0.5233 |
| 0.0434 | 2.0 | 825 | 0.0393 | 0.5159 |
| 0.0434 | 3.0 | 1237 | 0.0771 | 0.4967 |
| 0.0232 | 4.0 | 1650 | 0.0448 | 0.4959 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Jan 17, 2024
- Updated
- Jan 17, 2024