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AraT5v2-base-1024-finetune-ar-xlsum
This model is a fine-tuned version of UBC-NLP/AraT5v2-base-1024 on the xlsum dataset. It achieves the following results on the evaluation set:
- Loss: 3.7983
- Rouge-1: 33.4
- Rouge-2: 16.14
- Rouge-l: 29.31
- Gen Len: 18.63
- Bertscore: 74.57
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: 12
- eval_batch_size: 12
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 192
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- num_epochs: 10
- label_smoothing_factor: 0.1
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge-1 | Rouge-2 | Rouge-l | Gen Len | Bertscore |
|---|---|---|---|---|---|---|---|---|
| 6.1614 | 1.0 | 195 | 3.9898 | 28.51 | 12.02 | 24.64 | 18.87 | 72.64 |
| 4.5342 | 2.0 | 390 | 3.9048 | 29.5 | 13.01 | 25.85 | 18.53 | 73.34 |
| 4.2029 | 3.0 | 585 | 3.8162 | 31.64 | 14.33 | 27.54 | 18.57 | 73.88 |
| 3.9689 | 4.0 | 781 | 3.7949 | 31.87 | 14.56 | 27.9 | 18.55 | 74.04 |
| 3.8278 | 5.0 | 976 | 3.7702 | 31.85 | 14.58 | 27.74 | 18.74 | 73.96 |
| 3.6921 | 6.0 | 1171 | 3.7775 | 32.27 | 14.95 | 28.16 | 18.78 | 74.23 |
| 3.5632 | 7.0 | 1367 | 3.7751 | 32.54 | 15.04 | 28.4 | 18.72 | 74.36 |
| 3.493 | 8.0 | 1562 | 3.7815 | 32.35 | 14.95 | 28.24 | 18.71 | 74.32 |
| 3.4189 | 9.0 | 1757 | 3.7908 | 32.39 | 14.99 | 28.32 | 18.73 | 74.32 |
| 3.3492 | 9.98 | 1950 | 3.7983 | 32.6 | 15.19 | 28.5 | 18.72 | 74.35 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
