indosum-base-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: 0.7478
- Rouge1: 72.3325
- Rouge2: 65.1065
- Rougel: 69.2256
- Rougelsum: 71.5325
- Gen Len: 99.4045
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 |
---|---|---|---|---|---|---|---|---|
1.1904 | 1.0 | 892 | 0.8053 | 65.8257 | 57.6167 | 62.6222 | 65.0027 | 95.8598 |
0.6851 | 2.0 | 1784 | 0.6779 | 67.8889 | 60.0878 | 64.5868 | 66.9914 | 96.2911 |
0.4856 | 3.0 | 2676 | 0.6460 | 70.9241 | 63.6363 | 67.8555 | 70.153 | 96.9212 |
0.3358 | 4.0 | 3568 | 0.6565 | 69.9002 | 62.4 | 66.5928 | 69.0347 | 101.8745 |
0.1973 | 5.0 | 4460 | 0.7478 | 72.0587 | 64.7973 | 68.9279 | 71.3028 | 99.3765 |
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-1
Base model
LazarusNLP/IndoNanoT5-base