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---
license: apache-2.0
tags:
- summarization
- generated_from_trainer
datasets:
- wiki_lingua
model-index:
- name: mt5-base-finetuned-ar-wikilingua
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. -->
# mt5-base-finetuned-ar-wikilingua
This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the wiki_lingua dataset.
It achieves the following results on the evaluation set:
- Loss: 3.6790
- Rouge-1: 19.46
- Rouge-2: 6.82
- Rouge-l: 17.57
- Gen Len: 18.83
- Bertscore: 70.18
## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- num_epochs: 8
- label_smoothing_factor: 0.1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge-1 | Rouge-2 | Rouge-l | Gen Len | Bertscore |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:-------:|:---------:|
| 4.9783 | 1.0 | 5111 | 4.0107 | 15.8 | 4.65 | 14.18 | 18.98 | 68.66 |
| 4.2093 | 2.0 | 10222 | 3.8664 | 16.46 | 5.17 | 15.08 | 18.91 | 68.5 |
| 4.0303 | 3.0 | 15333 | 3.7847 | 17.0 | 5.43 | 15.45 | 18.89 | 68.75 |
| 3.9165 | 4.0 | 20444 | 3.7405 | 17.03 | 5.5 | 15.45 | 18.86 | 68.78 |
| 3.8396 | 5.0 | 25555 | 3.7102 | 17.14 | 5.57 | 15.48 | 18.87 | 68.92 |
| 3.7825 | 6.0 | 30666 | 3.6944 | 17.64 | 5.73 | 15.96 | 18.82 | 69.14 |
| 3.7447 | 7.0 | 35777 | 3.6801 | 17.6 | 5.66 | 15.9 | 18.78 | 69.23 |
| 3.7203 | 8.0 | 40888 | 3.6790 | 17.94 | 5.81 | 16.21 | 18.81 | 69.29 |
### Framework versions
- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.1.0
- Tokenizers 0.12.1
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