metadata
language:
- id
license: apache-2.0
base_model: LazarusNLP/IndoNanoT5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: summarization-lora-3
results: []
summarization-lora-3
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: 0.5212
- Rouge1: 0.3932
- Rouge2: 0.0
- Rougel: 0.3893
- Rougelsum: 0.3908
- Gen Len: 1.0
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 |
|---|---|---|---|---|---|---|---|---|
| 0.8224 | 1.0 | 892 | 0.5704 | 0.6572 | 0.0 | 0.6564 | 0.655 | 1.0 |
| 0.6196 | 2.0 | 1784 | 0.5431 | 0.6602 | 0.0 | 0.6579 | 0.6606 | 1.0 |
| 0.5778 | 3.0 | 2676 | 0.5373 | 0.6757 | 0.0 | 0.6756 | 0.6745 | 1.0 |
| 0.5503 | 4.0 | 3568 | 0.5256 | 0.659 | 0.0 | 0.6569 | 0.6586 | 1.0 |
| 0.5343 | 5.0 | 4460 | 0.5212 | 0.6659 | 0.0 | 0.6648 | 0.6661 | 1.0 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1