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mT5_multilingual_XLSum-finetune-ar-xlsum
This model is a fine-tuned version of csebuetnlp/mT5_multilingual_XLSum on the xlsum dataset. It achieves the following results on the evaluation set:
- Loss: 3.2497
- Rouge-1: 32.52
- Rouge-2: 14.71
- Rouge-l: 27.88
- Gen Len: 41.45
- Bertscore: 74.65
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: 16
- total_train_batch_size: 64
- 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 |
|---|---|---|---|---|---|---|---|---|
| 3.5465 | 1.0 | 585 | 3.3215 | 30.09 | 13.23 | 26.07 | 36.31 | 73.97 |
| 3.3564 | 2.0 | 1170 | 3.2547 | 31.29 | 13.93 | 26.75 | 41.68 | 74.22 |
| 3.2185 | 3.0 | 1755 | 3.2421 | 31.78 | 14.1 | 27.07 | 41.64 | 74.4 |
| 3.1145 | 4.0 | 2340 | 3.2241 | 31.98 | 14.38 | 27.51 | 40.29 | 74.46 |
| 3.031 | 5.0 | 2925 | 3.2313 | 32.3 | 14.67 | 27.83 | 39.81 | 74.61 |
| 2.9627 | 6.0 | 3510 | 3.2348 | 32.39 | 14.65 | 27.76 | 40.02 | 74.6 |
| 2.9088 | 7.0 | 4095 | 3.2439 | 32.5 | 14.66 | 27.81 | 41.2 | 74.65 |
| 2.8649 | 8.0 | 4680 | 3.2497 | 32.52 | 14.71 | 27.88 | 41.45 | 74.65 |
Framework versions
- Transformers 4.19.4
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
