---
license: apache-2.0
base_model: LazarusNLP/IndoNanoT5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: summarization-base-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-base-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: 0.4923
- Rouge1: 0.3905
- Rouge2: 0.0
- Rougel: 0.3898
- Rougelsum: 0.3916
- 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: 4
- eval_batch_size: 8
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 0.6327        | 1.0   | 3567  | 0.4634          | 0.3795 | 0.0    | 0.3806 | 0.3802    | 1.0     |
| 0.4349        | 2.0   | 7134  | 0.4541          | 0.3596 | 0.0    | 0.3615 | 0.3631    | 1.0     |
| 0.3376        | 3.0   | 10701 | 0.4562          | 0.4121 | 0.0    | 0.4123 | 0.4116    | 1.0     |
| 0.2683        | 4.0   | 14268 | 0.4744          | 0.3886 | 0.0    | 0.3869 | 0.388     | 1.0     |
| 0.2208        | 5.0   | 17835 | 0.4923          | 0.3905 | 0.0    | 0.3898 | 0.3916    | 1.0     |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1