indosum-lora-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: 0.5017
- Rouge1: 73.2585
- Rouge2: 66.378
- Rougel: 70.2761
- Rougelsum: 72.4613
- Gen Len: 102.6021
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 |
---|---|---|---|---|---|---|---|---|
0.7824 | 1.0 | 892 | 0.5557 | 70.0617 | 62.6298 | 66.9506 | 69.2215 | 103.8571 |
0.6003 | 2.0 | 1784 | 0.5394 | 70.7684 | 63.445 | 67.6025 | 69.9195 | 102.4539 |
0.5559 | 3.0 | 2676 | 0.5173 | 72.718 | 65.7162 | 69.7084 | 71.9054 | 102.0601 |
0.5274 | 4.0 | 3568 | 0.5044 | 72.4621 | 65.4284 | 69.4763 | 71.685 | 103.5300 |
0.5052 | 5.0 | 4460 | 0.5017 | 72.8123 | 65.8699 | 69.8629 | 72.0214 | 102.3445 |
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-1
Base model
LazarusNLP/IndoNanoT5-base