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xmod-roberta-base-legal-multi-eulegislation-downstream-eurlex
MHGanainy/xmod-roberta-base-legal-multi-eulegislation-downstream-eurlex
xmod-roberta-base-legal-multi-eulegislation-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
- xmod
- Access
- Public
- Created
- Aug 24, 2024
- Updated
- Aug 24, 2024
- SHA
- 74cacb42
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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. -->
xmod-roberta-base-legal-multi-eulegislation-downstream-eurlex
This model is a fine-tuned version of MHGanainy/xmod-roberta-base-legal-multi on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0738
- Macro-f1: 0.3582
- Micro-f1: 0.7157
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 |
|---|---|---|---|---|---|
| 0.074 | 1.0 | 3438 | 0.0798 | 0.3053 | 0.6923 |
| 0.0607 | 2.0 | 6876 | 0.0738 | 0.3582 | 0.7157 |
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
- xmod
- Created
- Aug 24, 2024
- Updated
- Aug 24, 2024