---
license: bigscience-bloom-rail-1.0
tags:
- generated_from_trainer
model-index:
- name: bloom-560m-finetuned-cdn_law
  results: []
---

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# Canadian Appellate Judgement Model

This model is a fine-tuned version of [bigscience/bloom-560m](https://huggingface.co/bigscience/bloom-560m) on Canadian appellate decisions (Ontario Court of Appeal and the British Columbia Court of Appeal) found in the [Pile of Law](https://huggingface.co/datasets/pile-of-law/pile-of-law) dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0135

## Intended uses & limitations

This model is intended to facilitate research into large language models and legal reasoning. It is not intended for use in any legal domain or to support legal work .

## Training procedure

This model was trained using the methodology set out in this [notebook](https://huggingface.co/docs/transformers/training).

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 2.1285        | 1.0   | 8298  | 2.0347          |
| 1.7999        | 2.0   | 16596 | 1.9876          |
| 1.6069        | 3.0   | 24894 | 2.0135          |


### Framework versions

- Transformers 4.23.1
- Pytorch 1.11.0
- Datasets 2.5.2
- Tokenizers 0.13.1