---
license: mit
base_model: nsi319/legal-led-base-16384
tags:
- generated_from_trainer
datasets:
- joelniklaus/legal_case_document_summarization
model-index:
- name: results
  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. -->

# results

This model is a fine-tuned version of [nsi319/legal-led-base-16384](https://huggingface.co/nsi319/legal-led-base-16384) on the joelniklaus/legal_case_document_summarization dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2570

## 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: 5e-05
- train_batch_size: 6
- eval_batch_size: 6
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.2213        | 1.0   | 1283 | 2.3223          |
| 2.1073        | 2.0   | 2566 | 2.2570          |


### Framework versions

- Transformers 4.36.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.15.0