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---
license: bigscience-bloom-rail-1.0
tags:
- generated_from_trainer
model-index:
- name: bloom-560m-finetuned-cdn_law
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. -->
# 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
|