---
license: mit
base_model: facebook/mbart-large-50
tags:
- generated_from_trainer
metrics:
- rouge
- sacrebleu
model-index:
- name: mBART-TextSimp-LT-BatchSize2-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-BatchSize2-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: 0.0962
- Rouge1: 0.76
- Rouge2: 0.6246
- Rougel: 0.7508
- Sacrebleu: 53.9078
- Gen Len: 32.9976

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 0.0639        | 1.0   | 418  | 0.0779          | 0.7012 | 0.5432 | 0.6904 | 43.0798   | 32.9976 |
| 0.0653        | 2.0   | 836  | 0.0732          | 0.7197 | 0.5593 | 0.7091 | 44.8483   | 32.9976 |
| 0.0327        | 3.0   | 1254 | 0.0726          | 0.7319 | 0.5787 | 0.7206 | 47.842    | 32.9976 |
| 0.0168        | 4.0   | 1672 | 0.0782          | 0.7466 | 0.6031 | 0.7371 | 50.9225   | 32.9976 |
| 0.013         | 5.0   | 2090 | 0.0804          | 0.7507 | 0.6077 | 0.7409 | 51.8293   | 32.9976 |
| 0.0032        | 6.0   | 2508 | 0.0846          | 0.7606 | 0.6237 | 0.7507 | 53.5224   | 32.9976 |
| 0.0012        | 7.0   | 2926 | 0.0911          | 0.7597 | 0.6263 | 0.751  | 54.0182   | 32.9976 |
| 0.0012        | 8.0   | 3344 | 0.0962          | 0.76   | 0.6246 | 0.7508 | 53.9078   | 32.9976 |


### Framework versions

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