summarization-pt-4
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: 1.2774
- Rouge1: 0.403
- Rouge2: 0.0
- Rougel: 0.4021
- Rougelsum: 0.405
- 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 |
---|---|---|---|---|---|---|---|---|
3.0347 | 1.0 | 892 | 2.0002 | 0.6717 | 0.0 | 0.6744 | 0.6696 | 1.0 |
2.4012 | 2.0 | 1784 | 1.7296 | 0.7117 | 0.0 | 0.7105 | 0.7111 | 1.0 |
2.1461 | 3.0 | 2676 | 1.4790 | 0.6953 | 0.0 | 0.6922 | 0.6902 | 1.0 |
1.952 | 4.0 | 3568 | 1.3589 | 0.6758 | 0.0 | 0.6753 | 0.6736 | 1.0 |
1.8052 | 5.0 | 4460 | 1.2774 | 0.6685 | 0.0 | 0.6677 | 0.6651 | 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-4
Base model
LazarusNLP/IndoNanoT5-base