summarization-pt-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: 1.3436
- Rouge1: 0.3954
- Rouge2: 0.0
- Rougel: 0.3954
- Rougelsum: 0.3942
- 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 |
---|---|---|---|---|---|---|---|---|
3.0294 | 1.0 | 892 | 1.9919 | 0.672 | 0.0 | 0.6729 | 0.6683 | 1.0 |
2.4162 | 2.0 | 1784 | 1.7555 | 0.7269 | 0.0 | 0.7253 | 0.727 | 1.0 |
2.1684 | 3.0 | 2676 | 1.5470 | 0.693 | 0.0 | 0.6917 | 0.6933 | 1.0 |
1.9893 | 4.0 | 3568 | 1.4300 | 0.6992 | 0.0 | 0.6959 | 0.6968 | 1.0 |
1.8466 | 5.0 | 4460 | 1.3436 | 0.6802 | 0.0 | 0.6802 | 0.6778 | 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-0
Base model
LazarusNLP/IndoNanoT5-base