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---
license: cc
base_model: joelniklaus/legal-xlm-roberta-base
tags:
- generated_from_trainer
model-index:
- name: bert-leg-al-corpus
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. -->
# bert-leg-al-corpus
This model is a fine-tuned version of [joelniklaus/legal-xlm-roberta-base](https://huggingface.co/joelniklaus/legal-xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7948
## 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-06
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.8679 | 0.4219 | 100 | 1.8208 |
| 1.8623 | 0.8439 | 200 | 1.8081 |
| 1.8987 | 1.2658 | 300 | 1.8153 |
| 1.8659 | 1.6878 | 400 | 1.7836 |
| 1.8685 | 2.1097 | 500 | 1.7825 |
| 1.8734 | 2.5316 | 600 | 1.7903 |
| 1.9124 | 2.9536 | 700 | 1.7771 |
| 1.8875 | 3.3755 | 800 | 1.7819 |
| 1.9029 | 3.7975 | 900 | 1.8032 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
|