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RuleBert-v0.3-k2
ribesstefano/RuleBert-v0.3-k2
RuleBert-v0.3-k2 is a text classification model from ribesstefano. 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
- Jan 7, 2024
- Updated
- Jan 7, 2024
- SHA
- d453504d
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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. -->
ribesstefano/RuleBert-v0.3-k2
This model is a fine-tuned version of papluca/xlm-roberta-base-language-detection on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3031
- F1: 0.5103
- Roc Auc: 0.6747
- Accuracy: 0.0
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: 5e-06
- train_batch_size: 2
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 8000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| 0.452 | 0.06 | 250 | 0.3816 | 0.5227 | 0.6861 | 0.0 |
| 0.3694 | 0.12 | 500 | 0.3191 | 0.5103 | 0.6747 | 0.0 |
| 0.3523 | 0.18 | 750 | 0.3031 | 0.5103 | 0.6747 | 0.0 |
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
- xlm-roberta
- License
- mit
- Created
- Jan 7, 2024
- Updated
- Jan 7, 2024