indosum-base-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: 0.6288
- Rouge1: 72.0825
- Rouge2: 64.9891
- Rougel: 69.2273
- Rougelsum: 71.1983
- Gen Len: 98.2637
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 |
---|---|---|---|---|---|---|---|---|
1.1965 | 1.0 | 892 | 0.7377 | 66.7755 | 58.7089 | 63.5735 | 65.9275 | 101.1593 |
0.691 | 2.0 | 1784 | 0.6472 | 70.9085 | 63.6467 | 67.9945 | 70.0311 | 100.5703 |
0.4907 | 3.0 | 2676 | 0.6098 | 70.4573 | 63.2612 | 67.6711 | 69.6221 | 96.9545 |
0.3404 | 4.0 | 3568 | 0.6288 | 71.5505 | 64.3094 | 68.674 | 70.6452 | 97.5743 |
0.2018 | 5.0 | 4460 | 0.6917 | 70.7161 | 63.2661 | 67.7431 | 69.8153 | 98.4471 |
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-4
Base model
LazarusNLP/IndoNanoT5-base