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---
language:
- id
license: apache-2.0
base_model: LazarusNLP/IndoNanoT5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: summarization-lora-2
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# summarization-lora-2
This model is a fine-tuned version of [LazarusNLP/IndoNanoT5-base](https://huggingface.co/LazarusNLP/IndoNanoT5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5532
- Rouge1: 0.3696
- Rouge2: 0.0
- Rougel: 0.3694
- Rougelsum: 0.3713
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 1.3998 | 1.0 | 1787 | 0.6384 | 0.3848 | 0.0 | 0.3845 | 0.3857 | 1.0 |
| 0.8601 | 2.0 | 3574 | 0.5793 | 0.391 | 0.0 | 0.391 | 0.3923 | 1.0 |
| 0.7972 | 3.0 | 5361 | 0.5576 | 0.3776 | 0.0 | 0.3767 | 0.3768 | 1.0 |
| 0.7698 | 4.0 | 7148 | 0.5620 | 0.3579 | 0.0 | 0.3565 | 0.3592 | 1.0 |
| 0.7566 | 5.0 | 8935 | 0.5532 | 0.3696 | 0.0 | 0.3694 | 0.3713 | 1.0 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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