summarization-pt-2
This model is a fine-tuned version of LazarusNLP/IndoNanoT5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.2686
- Rouge1: 0.4301
- Rouge2: 0.0
- Rougel: 0.4298
- Rougelsum: 0.4299
- Gen Len: 1.0
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: 0.001
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
---|---|---|---|---|---|---|---|---|
3.0441 | 1.0 | 894 | 1.9891 | 0.6966 | 0.0 | 0.698 | 0.6962 | 1.0 |
2.4037 | 2.0 | 1788 | 1.6702 | 0.7078 | 0.0 | 0.7135 | 0.7146 | 1.0 |
2.1345 | 3.0 | 2682 | 1.4640 | 0.6592 | 0.0 | 0.66 | 0.6572 | 1.0 |
1.9436 | 4.0 | 3576 | 1.3521 | 0.6535 | 0.0 | 0.6545 | 0.6547 | 1.0 |
1.7989 | 5.0 | 4470 | 1.2686 | 0.6818 | 0.0 | 0.6864 | 0.6834 | 1.0 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
Model tree for apwic/summarization-pt-2
Base model
LazarusNLP/IndoNanoT5-base
Finetuned
this model