indosum-base-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: 0.6175
- Rouge1: 72.8333
- Rouge2: 66.3463
- Rougel: 70.0278
- Rougelsum: 72.0501
- Gen Len: 97.6051
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 |
---|---|---|---|---|---|---|---|---|
1.2107 | 1.0 | 894 | 0.7716 | 66.2818 | 58.8499 | 63.3826 | 65.4963 | 106.3440 |
0.6904 | 2.0 | 1788 | 0.6373 | 72.0398 | 65.3647 | 69.1761 | 71.211 | 100.4793 |
0.4894 | 3.0 | 2682 | 0.6036 | 71.7057 | 65.1188 | 68.8683 | 70.8645 | 98.3481 |
0.3369 | 4.0 | 3576 | 0.6175 | 72.2133 | 65.6425 | 69.3517 | 71.4102 | 97.7162 |
0.1982 | 5.0 | 4470 | 0.7000 | 72.1304 | 65.3551 | 69.0923 | 71.291 | 98.3614 |
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/indosum-base-2
Base model
LazarusNLP/IndoNanoT5-base