---
language:
- id
license: apache-2.0
base_model: LazarusNLP/IndoNanoT5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: summarization-lora-4
  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-4

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: 0.4733
- 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