---
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