indosum-seq_bn-rf16-0
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: 0.4868
- Rouge1: 73.4412
- Rouge2: 66.5198
- Rougel: 70.4596
- Rougelsum: 72.5706
- Gen Len: 103.0
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 |
---|---|---|---|---|---|---|---|---|
0.7747 | 1.0 | 892 | 0.5280 | 70.368 | 63.1479 | 67.3463 | 69.4649 | 100.8813 |
0.6074 | 2.0 | 1784 | 0.5154 | 71.3426 | 64.1849 | 68.288 | 70.4796 | 104.6013 |
0.5576 | 3.0 | 2676 | 0.4920 | 71.6471 | 64.5469 | 68.6561 | 70.7418 | 101.8973 |
0.5199 | 4.0 | 3568 | 0.4931 | 72.695 | 65.8499 | 69.8428 | 71.8427 | 103.6333 |
0.4895 | 5.0 | 4460 | 0.4868 | 73.1452 | 66.2201 | 70.1397 | 72.2952 | 102.3827 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
Model tree for apwic/indosum-seq_bn-rf16-0
Base model
LazarusNLP/IndoNanoT5-base