---
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: 0.4683
- Rouge1: 0.3952
- Rouge2: 0.0
- Rougel: 0.3892
- Rougelsum: 0.3933
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 0.7823        | 1.0   | 894  | 0.5092          | 0.6551 | 0.0    | 0.6537 | 0.6535    | 1.0     |
| 0.6005        | 2.0   | 1788 | 0.4769          | 0.6706 | 0.0    | 0.6693 | 0.6688    | 1.0     |
| 0.5564        | 3.0   | 2682 | 0.4768          | 0.6725 | 0.0    | 0.6709 | 0.6731    | 1.0     |
| 0.5269        | 4.0   | 3576 | 0.4667          | 0.6722 | 0.0    | 0.6726 | 0.6742    | 1.0     |
| 0.5061        | 5.0   | 4470 | 0.4683          | 0.6725 | 0.0    | 0.6711 | 0.6719    | 1.0     |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1