metadata
language:
- id
license: apache-2.0
base_model: LazarusNLP/IndoNanoT5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: summarization-lora-2
results: []
summarization-lora-2
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: 0.5351
- Rouge1: 0.3585
- Rouge2: 0.0
- Rougel: 0.3555
- Rougelsum: 0.357
- 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: 5e-05
- train_batch_size: 8
- 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 |
|---|---|---|---|---|---|---|---|---|
| 1.2329 | 1.0 | 1787 | 0.5976 | 0.3912 | 0.0 | 0.3916 | 0.392 | 1.0 |
| 0.7952 | 2.0 | 3574 | 0.5580 | 0.3919 | 0.0 | 0.3921 | 0.3921 | 1.0 |
| 0.7407 | 3.0 | 5361 | 0.5366 | 0.3893 | 0.0 | 0.3879 | 0.3866 | 1.0 |
| 0.7152 | 4.0 | 7148 | 0.5402 | 0.354 | 0.0 | 0.3512 | 0.3523 | 1.0 |
| 0.7029 | 5.0 | 8935 | 0.5351 | 0.3585 | 0.0 | 0.3555 | 0.357 | 1.0 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1