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---
license: cc-by-sa-4.0
base_model: nlpaueb/legal-bert-small-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: scotus-v10
results: []
---
<!-- 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. -->
# scotus-v10
This model is a fine-tuned version of [nlpaueb/legal-bert-small-uncased](https://huggingface.co/nlpaueb/legal-bert-small-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7971
- Accuracy: 0.8842
## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.67 | 1.0 | 1219 | 1.3781 | 0.5718 |
| 1.1539 | 2.0 | 2438 | 0.9619 | 0.7077 |
| 0.6736 | 3.0 | 3657 | 0.7837 | 0.7668 |
| 0.4265 | 4.0 | 4876 | 0.5882 | 0.8309 |
| 0.2477 | 5.0 | 6095 | 0.5624 | 0.8446 |
| 0.1636 | 6.0 | 7314 | 0.5701 | 0.8542 |
| 0.0938 | 7.0 | 8533 | 0.6322 | 0.8603 |
| 0.0523 | 8.0 | 9752 | 0.6717 | 0.8606 |
| 0.0397 | 9.0 | 10971 | 0.6626 | 0.8738 |
| 0.0236 | 10.0 | 12190 | 0.6729 | 0.8811 |
| 0.0129 | 11.0 | 13409 | 0.7164 | 0.876 |
| 0.0098 | 12.0 | 14628 | 0.8041 | 0.8723 |
| 0.0066 | 13.0 | 15847 | 0.7792 | 0.8794 |
| 0.0055 | 14.0 | 17066 | 0.7704 | 0.8792 |
| 0.0032 | 15.0 | 18285 | 0.8369 | 0.8768 |
| 0.0023 | 16.0 | 19504 | 0.8685 | 0.8737 |
| 0.0012 | 17.0 | 20723 | 0.7631 | 0.888 |
| 0.0026 | 18.0 | 21942 | 0.8220 | 0.8808 |
| 0.0011 | 19.0 | 23161 | 0.7897 | 0.8845 |
| 0.0003 | 20.0 | 24380 | 0.7971 | 0.8842 |
### Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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