README.md

---
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: 1.8639

## 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: 24
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.408         | 0.6329 | 100  | 2.0952          |
| 2.1264        | 1.2658 | 200  | 1.9866          |
| 2.0701        | 1.8987 | 300  | 1.9136          |
| 2.0156        | 2.5316 | 400  | 1.8920          |
| 2.004         | 3.1646 | 500  | 1.8745          |
| 1.9702        | 3.7975 | 600  | 1.8537          |
| 1.9569        | 4.4304 | 700  | 1.8493          |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1