summarization-unipelt-1
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: 0.7109
- Rouge1: 0.4355
- Rouge2: 0.0
- Rougel: 0.436
- Rougelsum: 0.4342
- 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 |
---|---|---|---|---|---|---|---|---|
2.4406 | 1.0 | 892 | 1.2754 | 0.2408 | 0.0 | 0.2406 | 0.2405 | 1.0 |
1.5056 | 2.0 | 1784 | 0.9574 | 0.6755 | 0.0 | 0.6719 | 0.6802 | 1.0 |
1.2114 | 3.0 | 2676 | 0.8395 | 0.6067 | 0.0 | 0.6104 | 0.6102 | 1.0 |
1.0429 | 4.0 | 3568 | 0.7447 | 0.5115 | 0.0 | 0.5127 | 0.5115 | 1.0 |
0.9364 | 5.0 | 4460 | 0.7109 | 0.5511 | 0.0 | 0.5526 | 0.548 | 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-1
Base model
LazarusNLP/IndoNanoT5-base