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---
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