---
license: mit
base_model: facebook/mbart-large-50
tags:
- generated_from_trainer
metrics:
- rouge
- sacrebleu
model-index:
- name: mBART-TextSimp-LT-BatchSize4-lr5e-5
  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. -->

# mBART-TextSimp-LT-BatchSize4-lr5e-5

This model is a fine-tuned version of [facebook/mbart-large-50](https://huggingface.co/facebook/mbart-large-50) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0720
- Rouge1: 0.7898
- Rouge2: 0.643
- Rougel: 0.783
- Sacrebleu: 57.6148
- Gen Len: 33.6014

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Sacrebleu | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 0.407         | 1.0   | 209  | 0.1938          | 0.6481 | 0.4813 | 0.6379 | 42.027    | 33.6014 |
| 0.8377        | 2.0   | 418  | 0.1076          | 0.6446 | 0.4765 | 0.632  | 40.6092   | 33.7852 |
| 0.0589        | 3.0   | 627  | 0.0561          | 0.7659 | 0.6056 | 0.7581 | 51.836    | 33.6014 |
| 0.0237        | 4.0   | 836  | 0.0551          | 0.7816 | 0.6292 | 0.774  | 54.6775   | 33.6014 |
| 0.009         | 5.0   | 1045 | 0.0598          | 0.78   | 0.628  | 0.7723 | 54.4212   | 33.6014 |
| 0.0059        | 6.0   | 1254 | 0.0648          | 0.7876 | 0.6424 | 0.7805 | 56.5662   | 33.6014 |
| 0.003         | 7.0   | 1463 | 0.0694          | 0.7883 | 0.6405 | 0.781  | 57.3259   | 33.6014 |
| 0.0013        | 8.0   | 1672 | 0.0720          | 0.7898 | 0.643  | 0.783  | 57.6148   | 33.6014 |


### Framework versions

- Transformers 4.33.0
- Pytorch 2.1.2+cu121
- Datasets 2.14.4
- Tokenizers 0.13.3