led-risalah_data_v13
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.5198
- Rouge1 Precision: 0.4184
- Rouge1 Recall: 0.4032
- Rouge1 Fmeasure: 0.4092
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: 2e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 Fmeasure | Rouge1 Precision | Rouge1 Recall |
|---|---|---|---|---|---|---|
| 3.1517 | 0.9714 | 17 | 2.3560 | 0.2698 | 0.277 | 0.2642 |
| 2.2618 | 2.0 | 35 | 2.1487 | 0.3183 | 0.3295 | 0.3091 |
| 1.9714 | 2.9714 | 52 | 2.0826 | 0.3383 | 0.358 | 0.3226 |
| 1.8991 | 4.0 | 70 | 2.0284 | 0.34 | 0.3579 | 0.3248 |
| 1.7713 | 4.9714 | 87 | 1.9871 | 0.3667 | 0.3744 | 0.3602 |
| 1.7889 | 6.0 | 105 | 1.9714 | 0.3614 | 0.3729 | 0.3521 |
| 1.6378 | 6.9714 | 122 | 1.9481 | 0.3589 | 0.3762 | 0.3461 |
| 1.5649 | 8.0 | 140 | 1.9426 | 0.3657 | 0.3802 | 0.3545 |
| 1.5157 | 8.9714 | 157 | 1.9349 | 0.3667 | 0.375 | 0.361 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1
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