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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-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-BatchSize4-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: 0.0720
- Rouge1: 0.7898
- Rouge2: 0.643
- Rougel: 0.783
- Sacrebleu: 57.6148
- Gen Len: 33.6014
## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 0.407 | 1.0 | 209 | 0.1938 | 0.6481 | 0.4813 | 0.6379 | 42.027 | 33.6014 |
| 0.8377 | 2.0 | 418 | 0.1076 | 0.6446 | 0.4765 | 0.632 | 40.6092 | 33.7852 |
| 0.0589 | 3.0 | 627 | 0.0561 | 0.7659 | 0.6056 | 0.7581 | 51.836 | 33.6014 |
| 0.0237 | 4.0 | 836 | 0.0551 | 0.7816 | 0.6292 | 0.774 | 54.6775 | 33.6014 |
| 0.009 | 5.0 | 1045 | 0.0598 | 0.78 | 0.628 | 0.7723 | 54.4212 | 33.6014 |
| 0.0059 | 6.0 | 1254 | 0.0648 | 0.7876 | 0.6424 | 0.7805 | 56.5662 | 33.6014 |
| 0.003 | 7.0 | 1463 | 0.0694 | 0.7883 | 0.6405 | 0.781 | 57.3259 | 33.6014 |
| 0.0013 | 8.0 | 1672 | 0.0720 | 0.7898 | 0.643 | 0.783 | 57.6148 | 33.6014 |
### Framework versions
- Transformers 4.33.0
- Pytorch 2.1.2+cu121
- Datasets 2.14.4
- Tokenizers 0.13.3
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