summarization-unipelt-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: 0.6790
- Rouge1: 0.3961
- Rouge2: 0.0
- Rougel: 0.3992
- Rougelsum: 0.3996
- 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 |
---|---|---|---|---|---|---|---|---|
2.436 | 1.0 | 894 | 1.2680 | 0.0305 | 0.0 | 0.0305 | 0.0305 | 1.0 |
1.5097 | 2.0 | 1788 | 0.9426 | 0.0223 | 0.0 | 0.0223 | 0.0223 | 1.0 |
1.2078 | 3.0 | 2682 | 0.7915 | 0.1643 | 0.0 | 0.1641 | 0.1639 | 1.0 |
1.0371 | 4.0 | 3576 | 0.7170 | 0.2501 | 0.0 | 0.2524 | 0.2507 | 1.0 |
0.9294 | 5.0 | 4470 | 0.6790 | 0.304 | 0.0 | 0.3076 | 0.3081 | 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-2
Base model
LazarusNLP/IndoNanoT5-base