indosum-lora-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: 0.4698
- Rouge1: 73.8688
- Rouge2: 67.6187
- Rougel: 71.1566
- Rougelsum: 73.2002
- Gen Len: 101.4471
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 |
---|---|---|---|---|---|---|---|---|
0.7883 | 1.0 | 894 | 0.5147 | 70.9781 | 64.3792 | 68.0826 | 70.1936 | 98.6372 |
0.6044 | 2.0 | 1788 | 0.4863 | 72.663 | 66.2333 | 69.8132 | 71.9752 | 102.0187 |
0.5609 | 3.0 | 2682 | 0.4760 | 73.1913 | 66.8222 | 70.379 | 72.525 | 101.9304 |
0.5314 | 4.0 | 3576 | 0.4698 | 73.8131 | 67.3889 | 70.9754 | 73.0829 | 100.9786 |
0.5104 | 5.0 | 4470 | 0.4697 | 73.6281 | 67.2468 | 70.8416 | 72.906 | 100.8594 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
Model tree for apwic/indosum-lora-2
Base model
LazarusNLP/IndoNanoT5-base