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---
language:
- id
license: apache-2.0
base_model: LazarusNLP/IndoNanoT5-base
tags:
- generated_from_trainer
datasets:
- id_liputan6
metrics:
- rouge
model-index:
- name: liputan6-pt-pl50
results:
- task:
name: Summarization
type: summarization
dataset:
name: id_liputan6 canonical
type: id_liputan6
config: canonical
split: validation
args: canonical
metrics:
- name: Rouge1
type: rouge
value: 35.5686
---
<!-- 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. -->
# liputan6-pt-pl50
This model is a fine-tuned version of [LazarusNLP/IndoNanoT5-base](https://huggingface.co/LazarusNLP/IndoNanoT5-base) on the id_liputan6 canonical dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6722
- Rouge1: 35.5686
- Rouge2: 23.5102
- Rougel: 31.8451
- Rougelsum: 33.6584
- Gen Len: 49.748
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 4.2782 | 1.0 | 63 | 3.2600 | 25.0139 | 13.1669 | 22.4852 | 23.5026 | 38.037 |
| 3.3831 | 2.0 | 126 | 3.0118 | 28.0005 | 15.5199 | 25.1006 | 26.3175 | 51.621 |
| 3.0732 | 3.0 | 189 | 2.8226 | 31.6641 | 18.1569 | 27.8004 | 29.8463 | 51.938 |
| 2.83 | 4.0 | 252 | 2.7181 | 34.3328 | 21.5065 | 30.323 | 32.3623 | 51.327 |
| 2.6441 | 5.0 | 315 | 2.6722 | 34.8229 | 22.044 | 30.8324 | 33.0138 | 52.623 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
|