---
license: mit
base_model: facebook/mbart-large-50
tags:
- generated_from_trainer
metrics:
- rouge
- sacrebleu
model-index:
- name: mBART-TextSimp-LT-BatchSize4-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-BatchSize4-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: 0.0810
- Rouge1: 0.8026
- Rouge2: 0.6711
- Rougel: 0.796
- Sacrebleu: 55.7975
- Gen Len: 33.3938

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 0.0978        | 1.0   | 209  | 0.0948          | 0.6734 | 0.5117 | 0.664  | 43.1877   | 33.3938 |
| 0.0617        | 2.0   | 418  | 0.0598          | 0.7702 | 0.6222 | 0.7609 | 49.5794   | 33.3938 |
| 1.1021        | 3.0   | 627  | 0.8158          | 0.0161 | 0.0    | 0.0162 | 0.0009    | 34.3938 |
| 0.0471        | 4.0   | 836  | 0.0822          | 0.6874 | 0.5335 | 0.6779 | 44.9573   | 33.3938 |
| 0.0276        | 5.0   | 1045 | 0.0664          | 0.7767 | 0.6339 | 0.7686 | 52.2135   | 33.3938 |
| 0.0162        | 6.0   | 1254 | 0.0756          | 0.7856 | 0.6452 | 0.7796 | 50.4352   | 33.3938 |
| 0.0069        | 7.0   | 1463 | 0.0796          | 0.7939 | 0.6586 | 0.7877 | 52.9489   | 33.3938 |
| 0.0051        | 8.0   | 1672 | 0.0810          | 0.8026 | 0.6711 | 0.796  | 55.7975   | 33.3938 |


### Framework versions

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