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mt5-base-arabic
This model is a fine-tuned version of google/mt5-base on arabic subset on the xlsum dataset. It achieves the following results on the evaluation set:
- Loss: 3.2742
- Rouge-1: 22.86
- Rouge-2: 10.31
- Rouge-l: 20.85
- Gen Len: 19.0
- Bertscore: 71.52
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: 0.0005
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- label_smoothing_factor: 0.1
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge-1 | Rouge-2 | Rouge-l | Gen Len | Bertscore |
|---|---|---|---|---|---|---|---|---|
| 4.2331 | 1.0 | 1172 | 3.5051 | 18.54 | 6.63 | 16.77 | 19.0 | 70.28 |
| 3.7075 | 2.0 | 2344 | 3.3737 | 19.99 | 7.94 | 18.19 | 19.0 | 70.79 |
| 3.5132 | 3.0 | 3516 | 3.3171 | 20.76 | 8.57 | 18.96 | 19.0 | 70.95 |
| 3.3859 | 4.0 | 4688 | 3.2811 | 21.49 | 8.99 | 19.51 | 19.0 | 71.19 |
| 3.3012 | 5.0 | 5860 | 3.2742 | 21.79 | 9.18 | 19.77 | 19.0 | 71.25 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.11.0+cu113
- Datasets 2.1.0
- Tokenizers 0.12.1
