summarization-unipelt-3
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: 0.7173
- Rouge1: 0.4469
- Rouge2: 0.0
- Rougel: 0.4454
- Rougelsum: 0.4457
- 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 |
---|---|---|---|---|---|---|---|---|
2.4275 | 1.0 | 892 | 1.2781 | 0.1861 | 0.0 | 0.1881 | 0.1893 | 1.0 |
1.5017 | 2.0 | 1784 | 0.9698 | 0.2767 | 0.0 | 0.2791 | 0.2749 | 1.0 |
1.1964 | 3.0 | 2676 | 0.8235 | 0.2852 | 0.0 | 0.2836 | 0.2837 | 1.0 |
1.0261 | 4.0 | 3568 | 0.7468 | 0.4923 | 0.0 | 0.491 | 0.4914 | 1.0 |
0.9195 | 5.0 | 4460 | 0.7173 | 0.456 | 0.0 | 0.457 | 0.4597 | 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-unipelt-3
Base model
LazarusNLP/IndoNanoT5-base