indosum-lora-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: 0.4621
- Rouge1: 73.7537
- Rouge2: 67.0657
- Rougel: 71.1377
- Rougelsum: 72.9002
- Gen Len: 101.8929
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 |
---|---|---|---|---|---|---|---|---|
0.7838 | 1.0 | 892 | 0.5145 | 69.9783 | 62.8024 | 67.0786 | 69.0962 | 98.8206 |
0.6031 | 2.0 | 1784 | 0.4936 | 71.6523 | 64.7055 | 68.9409 | 70.7517 | 103.1459 |
0.5579 | 3.0 | 2676 | 0.4722 | 72.165 | 65.403 | 69.5451 | 71.3208 | 100.0388 |
0.5287 | 4.0 | 3568 | 0.4657 | 73.1062 | 66.416 | 70.5428 | 72.2864 | 99.8876 |
0.5074 | 5.0 | 4460 | 0.4621 | 73.4114 | 66.7459 | 70.7702 | 72.5939 | 101.6091 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
Model tree for apwic/indosum-lora-4
Base model
LazarusNLP/IndoNanoT5-base