---
license: mit
base_model: facebook/mbart-large-50
tags:
- generated_from_trainer
metrics:
- rouge
- sacrebleu
model-index:
- name: mBART-TextSimp-LT-BatchSize8-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-BatchSize8-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: 0.4296
- Rouge1: 0.0605
- Rouge2: 0.0078
- Rougel: 0.0593
- Sacrebleu: 0.044
- Gen Len: 34.5776

## 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: 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  |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:--------:|
| 8.0008        | 1.0   | 104  | 7.0565          | 0.1958 | 0.1282 | 0.1868 | 7.9463    | 511.6945 |
| 0.3454        | 2.0   | 209  | 0.1874          | 0.6646 | 0.4862 | 0.6559 | 41.0808   | 34.5752  |
| 0.0728        | 3.0   | 313  | 0.0748          | 0.7063 | 0.5426 | 0.6984 | 48.033    | 34.5752  |
| 0.0491        | 4.0   | 418  | 0.0630          | 0.7346 | 0.5861 | 0.7248 | 51.6574   | 34.5752  |
| 0.755         | 5.0   | 522  | 0.7158          | 0.0008 | 0.0    | 0.0009 | 0.0       | 35.5752  |
| 0.4913        | 6.0   | 627  | 0.4653          | 0.0218 | 0.0008 | 0.0219 | 0.022     | 34.6134  |
| 0.4771        | 7.0   | 731  | 0.4525          | 0.0385 | 0.0034 | 0.0382 | 0.0308    | 34.926   |
| 0.4224        | 7.96  | 832  | 0.4296          | 0.0605 | 0.0078 | 0.0593 | 0.044     | 34.5776  |


### Framework versions

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