summarization-base-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: 0.7586
- Rouge1: 0.3646
- Rouge2: 0.0
- Rougel: 0.3635
- Rougelsum: 0.3662
- 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 |
---|---|---|---|---|---|---|---|---|
1.2006 | 1.0 | 892 | 0.8184 | 0.6667 | 0.0 | 0.6667 | 0.6663 | 1.0 |
0.6791 | 2.0 | 1784 | 0.6924 | 0.6654 | 0.0 | 0.6613 | 0.6642 | 1.0 |
0.4848 | 3.0 | 2676 | 0.6634 | 0.7098 | 0.0 | 0.7089 | 0.7131 | 1.0 |
0.3381 | 4.0 | 3568 | 0.6800 | 0.696 | 0.0 | 0.6977 | 0.6988 | 1.0 |
0.2027 | 5.0 | 4460 | 0.7586 | 0.682 | 0.0 | 0.681 | 0.6795 | 1.0 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for apwic/summarization-base-3
Base model
LazarusNLP/IndoNanoT5-base