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mt5-base-finetuned-persian
This model is a fine-tuned version of google/mt5-base on the xlsum dataset. It achieves the following results on the evaluation set:
- Loss: 3.6086
- Rouge-1: 22.02
- Rouge-2: 7.41
- Rouge-l: 18.95
- Gen Len: 19.0
- Bertscore: 69.89
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 |
|---|---|---|---|---|---|---|---|---|
| 7.2823 | 0.96 | 19 | 3.9800 | 19.78 | 5.57 | 16.24 | 19.0 | 68.19 |
| 4.7334 | 1.96 | 38 | 3.7620 | 20.92 | 7.49 | 18.27 | 18.91 | 68.72 |
| 4.3891 | 2.96 | 57 | 3.6349 | 21.07 | 7.66 | 18.53 | 18.96 | 69.73 |
| 4.2 | 3.96 | 76 | 3.6315 | 19.63 | 6.49 | 16.61 | 19.0 | 69.15 |
| 3.9202 | 4.96 | 95 | 3.6086 | 21.2 | 6.8 | 17.06 | 19.0 | 69.48 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.11.0+cu113
- Datasets 2.1.0
- Tokenizers 0.12.1
