metadata
language:
- id
license: apache-2.0
base_model: LazarusNLP/IndoNanoT5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: summarization-lora-4
results: []
summarization-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: 0.4733
- Rouge1: 0.3767
- Rouge2: 0.0
- Rougel: 0.3787
- Rougelsum: 0.3802
- 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 |
---|---|---|---|---|---|---|---|---|
0.8225 | 1.0 | 892 | 0.5298 | 0.7091 | 0.0 | 0.7089 | 0.7076 | 1.0 |
0.623 | 2.0 | 1784 | 0.5064 | 0.7118 | 0.0 | 0.71 | 0.7093 | 1.0 |
0.5809 | 3.0 | 2676 | 0.4813 | 0.7155 | 0.0 | 0.7147 | 0.7119 | 1.0 |
0.5549 | 4.0 | 3568 | 0.4799 | 0.7058 | 0.0 | 0.7057 | 0.7028 | 1.0 |
0.5383 | 5.0 | 4460 | 0.4733 | 0.7008 | 0.0 | 0.7001 | 0.6968 | 1.0 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1