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---
license: apache-2.0
base_model: LazarusNLP/IndoNanoT5-base
tags:
- generated_from_trainer
language:
- ind
datasets:
- GEM/indonlg
metrics:
- bleu
- sacrebleu
model-index:
- name: IndoNanoT5-base-XPersona
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: indonlg
type: indonlg
config: xpersona
split: test
args: xpersona
metrics:
- name: Bleu
type: bleu
value: 4.0669
- name: Sacrebleu
type: sacrebleu
value: 4.0669
---
<!-- 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. -->
# LazarusNLP/IndoNanoT5-base-XPersona
This model is a fine-tuned version of [LazarusNLP/IndoNanoT5-base](https://huggingface.co/LazarusNLP/IndoNanoT5-base) on the indonlg dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8372
- Bleu: 4.0669
- Sacrebleu: 4.0669
## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Sacrebleu |
|:-------------:|:-----:|:------:|:---------------:|:------:|:---------:|
| 1.9872 | 1.0 | 15516 | 1.8482 | 3.7015 | 3.7015 |
| 1.888 | 2.0 | 31032 | 1.8434 | 4.0409 | 4.0409 |
| 1.8207 | 3.0 | 46548 | 1.8347 | 4.1239 | 4.1239 |
| 1.7716 | 4.0 | 62064 | 1.8340 | 4.3231 | 4.3231 |
| 1.6948 | 5.0 | 77580 | 1.8443 | 4.4283 | 4.4283 |
| 1.6442 | 6.0 | 93096 | 1.8563 | 4.5338 | 4.5338 |
| 1.5856 | 7.0 | 108612 | 1.8782 | 4.3033 | 4.3033 |
| 1.5451 | 8.0 | 124128 | 1.8930 | 4.3286 | 4.3286 |
| 1.5056 | 9.0 | 139644 | 1.9207 | 4.2773 | 4.2773 |
| 1.446 | 10.0 | 155160 | 1.9406 | 4.0629 | 4.0629 |
| 1.406 | 11.0 | 170676 | 1.9636 | 4.1382 | 4.1382 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu118
- Datasets 2.16.1
- Tokenizers 0.15.1
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