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roberta-large-finetuned-eurlex
ayushtak/roberta-large-finetuned-eurlex
roberta-large-finetuned-eurlex is a fill-mask model from ayushtak. Use it when you need the model to fill a missing word. 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
- Fill-Mask
- Library
- transformers
- License
- mit
- Model type
- roberta
- Access
- Public
- Created
- Jul 20, 2025
- Updated
- Jul 20, 2025
- SHA
- b6f00260
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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-eurlex
This model is a fine-tuned version of FacebookAI/roberta-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8688
- Model Preparation Time: 0.0052
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: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH 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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time |
|---|---|---|---|---|
| 1.0531 | 1.0 | 313 | 0.9418 | 0.0052 |
| 0.98 | 2.0 | 626 | 0.9087 | 0.0052 |
| 0.9311 | 3.0 | 939 | 0.8661 | 0.0052 |
Framework versions
- Transformers 4.53.2
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.2
- Task
- Fill-Mask
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Jul 20, 2025
- Updated
- Jul 20, 2025