---
library_name: transformers
license: mit
base_model: nsi319/legal-pegasus
tags:
- generated_from_trainer
model-index:
- name: bodoLegalPegasus
  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. -->

# bodoLegalPegasus

This model is a fine-tuned version of [nsi319/legal-pegasus](https://huggingface.co/nsi319/legal-pegasus) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7662

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 4

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 3.6251        | 1.0    | 313  | 3.5900          |
| 3.2344        | 2.0    | 626  | 3.1249          |
| 3.0194        | 3.0    | 939  | 2.8920          |
| 2.8709        | 3.9896 | 1248 | 2.7662          |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.0.1+cu117
- Datasets 3.2.0
- Tokenizers 0.21.0