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---
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
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