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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-base-2
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-2
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: 0.6973
- Rouge1: 0.3985
- Rouge2: 0.0
- Rougel: 0.3957
- Rougelsum: 0.3995
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 1.21 | 1.0 | 894 | 0.7570 | 0.6899 | 0.0 | 0.6953 | 0.6878 | 1.0 |
| 0.6826 | 2.0 | 1788 | 0.6250 | 0.6779 | 0.0 | 0.6777 | 0.6768 | 1.0 |
| 0.4899 | 3.0 | 2682 | 0.5915 | 0.6825 | 0.0 | 0.681 | 0.6837 | 1.0 |
| 0.3413 | 4.0 | 3576 | 0.6194 | 0.7341 | 0.0 | 0.7341 | 0.7373 | 1.0 |
| 0.2044 | 5.0 | 4470 | 0.6973 | 0.6972 | 0.0 | 0.6971 | 0.6984 | 1.0 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
|