---
license: mit
base_model: facebook/mbart-large-50
tags:
- generated_from_trainer
metrics:
- rouge
- sacrebleu
model-index:
- name: mBART-TextSimp-LT-BatchSize8-lr1e-4
  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-BatchSize8-lr1e-4

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: 0.0744
- Rouge1: 0.7931
- Rouge2: 0.657
- Rougel: 0.7873
- Sacrebleu: 56.7266
- Gen Len: 34.9093

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 5.5149        | 1.0   | 104  | 3.9238          | 0.6383 | 0.4681 | 0.6268 | 40.2914   | 36.6301 |
| 0.0989        | 2.0   | 209  | 0.0807          | 0.6925 | 0.5318 | 0.6852 | 46.8337   | 34.9093 |
| 0.0666        | 3.0   | 313  | 0.0679          | 0.7014 | 0.5448 | 0.6936 | 47.4249   | 34.9093 |
| 0.0464        | 4.0   | 418  | 0.0765          | 0.698  | 0.5344 | 0.6859 | 46.7217   | 34.9093 |
| 0.0344        | 5.0   | 522  | 0.0668          | 0.7604 | 0.6085 | 0.7526 | 49.5391   | 34.9117 |
| 0.0168        | 6.0   | 627  | 0.0652          | 0.7825 | 0.6391 | 0.7763 | 53.7888   | 34.9093 |
| 0.0116        | 7.0   | 731  | 0.0674          | 0.7911 | 0.6558 | 0.7856 | 55.8977   | 34.9093 |
| 0.0036        | 7.96  | 832  | 0.0744          | 0.7931 | 0.657  | 0.7873 | 56.7266   | 34.9093 |


### Framework versions

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