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roberta-base-legal-multi-downstream-eurlex
MHGanainy/roberta-base-legal-multi-downstream-eurlex
roberta-base-legal-multi-downstream-eurlex is a text classification model from MHGanainy. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- roberta
- Access
- Public
- Created
- Aug 24, 2024
- Updated
- Aug 24, 2024
- SHA
- 63a117d9
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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-base-legal-multi-downstream-eurlex
This model is a fine-tuned version of MHGanainy/roberta-base-legal-multi on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0737
- Macro-f1: 0.3592
- Micro-f1: 0.7181
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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 1
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Macro-f1 | Micro-f1 |
|---|---|---|---|---|---|
| 0.0739 | 1.0 | 3438 | 0.0801 | 0.3013 | 0.6902 |
| 0.0604 | 2.0 | 6876 | 0.0737 | 0.3592 | 0.7181 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- Created
- Aug 24, 2024
- Updated
- Aug 24, 2024