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---
license: mit
tags:
- summarization
- generated_from_trainer
datasets:
- ravkuk_summerize_dataset
metrics:
- rouge
model-index:
- name: le-fine-tune-mbart-large-50
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: ravkuk_summerize_dataset
type: ravkuk_summerize_dataset
config: default
split: train
args: default
metrics:
- name: Rouge1
type: rouge
value: 0.2928
---
<!-- 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. -->
# le-fine-tune-mbart-large-50
This model is a fine-tuned version of [facebook/mbart-large-50](https://huggingface.co/facebook/mbart-large-50) on the ravkuk_summerize_dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7762
- Rouge1: 0.2928
- Rouge2: 0.1926
- Rougel: 0.2815
- Rougelsum: 0.2816
- Gen Len: 34.5028
## 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: 5.6e-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
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 3.1169 | 1.0 | 197 | 2.3604 | 0.1878 | 0.0725 | 0.1737 | 0.1737 | 33.7784 |
| 1.8945 | 2.0 | 394 | 2.2522 | 0.1897 | 0.0765 | 0.1776 | 0.1776 | 34.2074 |
| 1.3083 | 3.0 | 591 | 2.2886 | 0.2001 | 0.0927 | 0.1895 | 0.1892 | 35.4432 |
| 0.8693 | 4.0 | 788 | 2.3727 | 0.2243 | 0.1123 | 0.2122 | 0.2117 | 31.4943 |
| 0.5507 | 5.0 | 985 | 2.5059 | 0.2577 | 0.1527 | 0.2463 | 0.2466 | 34.3693 |
| 0.3385 | 6.0 | 1182 | 2.6032 | 0.2703 | 0.1672 | 0.2593 | 0.2584 | 33.5994 |
| 0.2031 | 7.0 | 1379 | 2.6518 | 0.2912 | 0.1932 | 0.2812 | 0.281 | 34.1676 |
| 0.1272 | 8.0 | 1576 | 2.7040 | 0.2891 | 0.1895 | 0.2799 | 0.2796 | 34.6761 |
| 0.0842 | 9.0 | 1773 | 2.7515 | 0.2978 | 0.198 | 0.2888 | 0.2887 | 34.1932 |
| 0.0605 | 10.0 | 1970 | 2.7762 | 0.2928 | 0.1926 | 0.2815 | 0.2816 | 34.5028 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
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