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fine_tuned_model_on_SJP_dataset_de_balanced_2048_tokens
mhmmterts/fine_tuned_model_on_SJP_dataset_de_balanced_2048_tokens
fine_tuned_model_on_SJP_dataset_de_balanced_2048_tokens is a text classification model from mhmmterts. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as cc.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- cc
- Model type
- roberta
- Access
- Public
- Created
- Feb 27, 2024
- Updated
- Feb 27, 2024
- SHA
- 8136bc8c
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Base models
Datasets
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. -->
fine_tuned_model_on_SJP_dataset_de_balanced_2048_tokens
This model is a fine-tuned version of joelniklaus/legal-swiss-roberta-large on the swiss_judgment_prediction dataset. It achieves the following results on the evaluation set:
- Loss: 0.6456
- Accuracy: 0.8031
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6562 | 1.0 | 8865 | 0.6456 | 0.8031 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu118
- Datasets 2.17.0
- Tokenizers 0.15.1
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- cc
- Created
- Feb 27, 2024
- Updated
- Feb 27, 2024