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---
license: cc-by-sa-4.0
base_model: nlpaueb/legal-bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: partisan-legal-bert-base-uncased-supreme-court-32batch_5epoch_2e5lr_1wd
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. -->
# partisan-legal-bert-base-uncased-supreme-court-32batch_5epoch_2e5lr_1wd
This model is a fine-tuned version of [nlpaueb/legal-bert-base-uncased](https://huggingface.co/nlpaueb/legal-bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7014
- Accuracy: 0.6763
## 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: 32
- eval_batch_size: 32
- seed: 7
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6555 | 1.0 | 660 | 0.5453 | 0.6563 |
| 0.603 | 2.0 | 1320 | 0.5560 | 0.67 |
| 0.5715 | 3.0 | 1980 | 0.5691 | 0.6641 |
| 0.4327 | 4.0 | 2640 | 0.6462 | 0.6648 |
| 0.3684 | 5.0 | 3300 | 0.7014 | 0.6763 |
### Framework versions
- Transformers 4.35.1
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
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