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MiniLM-L12-H384-legal-classification
IndranilB/MiniLM-L12-H384-legal-classification
MiniLM-L12-H384-legal-classification is a text classification model from IndranilB. 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
- bert
- Access
- Public
- Created
- Jul 10, 2026
- Updated
- Jul 10, 2026
- SHA
- 39cd0e92
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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. -->
MiniLM-L12-H384-legal-classification
This model is a fine-tuned version of microsoft/MiniLM-L12-H384-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.9404
- Accuracy: 0.4945
- Micro F1: 0.4945
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: 128
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 256
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Micro F1 |
|---|---|---|---|---|---|
| 9.1142 | 1.0 | 159 | 4.4392 | 0.3690 | 0.3690 |
| 8.3566 | 2.0 | 318 | 4.0737 | 0.4793 | 0.4793 |
| 7.9217 | 3.0 | 477 | 3.9404 | 0.4945 | 0.4945 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 5.0.0
- Tokenizers 0.22.2
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- mit
- Created
- Jul 10, 2026
- Updated
- Jul 10, 2026