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---
language:
- id
license: apache-2.0
base_model: LazarusNLP/IndoNanoT5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: summarization-seq_bn-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-seq_bn-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: 0.4653
- Rouge1: 0.3992
- Rouge2: 0.0
- Rougel: 0.4016
- Rougelsum: 0.4001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 0.7807 | 1.0 | 892 | 0.5299 | 0.6861 | 0.0 | 0.6833 | 0.6836 | 1.0 |
| 0.6079 | 2.0 | 1784 | 0.4989 | 0.7141 | 0.0 | 0.7153 | 0.7147 | 1.0 |
| 0.5583 | 3.0 | 2676 | 0.4761 | 0.7153 | 0.0 | 0.7152 | 0.7139 | 1.0 |
| 0.5208 | 4.0 | 3568 | 0.4719 | 0.7433 | 0.0 | 0.743 | 0.7395 | 1.0 |
| 0.4912 | 5.0 | 4460 | 0.4653 | 0.7309 | 0.0 | 0.7284 | 0.7264 | 1.0 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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