bert2bert-canonicalcleandata-extremecleandata-dropout-0.3-lr-5e-05
- Dev set: Canonical clean data
- Add more train with extreme dev set data 5 epoch
- Encoder max length (input): 512
- Decoder max length (output): 512
This model was trained from scratch on the id_liputan6 dataset. It achieves the following results on the evaluation set:
- Loss: 2.4528
- Rouge2 Precision: 0.1519
- Rouge2 Recall: 0.1497
- Rouge2 Fmeasure: 0.1496
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: 5e-05
- dropout: 0.3
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
---|---|---|---|---|---|---|
2.6029 | 1.0 | 619 | 2.2821 | 0.1605 | 0.1573 | 0.1576 |
2.2629 | 2.0 | 1238 | 2.3146 | 0.1566 | 0.1588 | 0.1565 |
2.028 | 3.0 | 1857 | 2.3690 | 0.1548 | 0.1513 | 0.1519 |
1.8267 | 4.0 | 2476 | 2.4174 | 0.1527 | 0.1491 | 0.1497 |
1.5451 | 5.0 | 3095 | 2.4528 | 0.1519 | 0.1497 | 0.1496 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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