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legalcase_outcome_model_v3
Othniel74/legalcase_outcome_model_v3
legalcase_outcome_model_v3 is a text classification model from Othniel74. 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-by-sa-4.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- cc-by-sa-4.0
- Model type
- bert
- Access
- Public
- Created
- Sep 26, 2024
- Updated
- Sep 26, 2024
- SHA
- b23fa445
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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. -->
legalcase_outcome_model_v3
This model is a fine-tuned version of nlpaueb/legal-bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.8798
- Accuracy: 0.3441
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5962 | 1.0 | 224 | 2.5266 | 0.3533 |
| 0.5769 | 2.0 | 448 | 2.7836 | 0.3472 |
| 0.4587 | 3.0 | 672 | 2.8798 | 0.3441 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0
- Datasets 3.0.0
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- cc-by-sa-4.0
- Created
- Sep 26, 2024
- Updated
- Sep 26, 2024