---
license: apache-2.0
base_model: LazarusNLP/IndoNanoT5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: summarization-lora-1
  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-1

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: 0.5838
- Rouge1: 0.5174
- Rouge2: 0.0
- Rougel: 0.523
- Rougelsum: 0.5165
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 1.3911        | 1.0   | 1783 | 0.6611          | 0.4074 | 0.0    | 0.4062 | 0.4066    | 1.0     |
| 0.8526        | 2.0   | 3566 | 0.6167          | 0.5108 | 0.0    | 0.515  | 0.51      | 1.0     |
| 0.7928        | 3.0   | 5349 | 0.5968          | 0.4966 | 0.0    | 0.5042 | 0.4969    | 1.0     |
| 0.7651        | 4.0   | 7132 | 0.5860          | 0.5171 | 0.0    | 0.5228 | 0.5173    | 1.0     |
| 0.7528        | 5.0   | 8915 | 0.5838          | 0.5174 | 0.0    | 0.523  | 0.5165    | 1.0     |


### Framework versions

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