Model save
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README.md
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---
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language:
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license: apache-2.0
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base_model: LazarusNLP/IndoNanoT5-base
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tags:
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This model is a fine-tuned version of [LazarusNLP/IndoNanoT5-base](https://huggingface.co/LazarusNLP/IndoNanoT5-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Rouge1: 0.
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- Rouge2: 0.0
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- Rougel: 0.
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- Rougelsum: 0.
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- Gen Len: 1.0
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate:
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- train_batch_size:
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- eval_batch_size:
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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### Training results
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| Training Loss | Epoch | Step
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### Framework versions
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- Transformers 4.40.2
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- Pytorch 2.3.
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- Datasets 2.
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- Tokenizers 0.19.1
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---
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license: apache-2.0
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base_model: LazarusNLP/IndoNanoT5-base
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tags:
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This model is a fine-tuned version of [LazarusNLP/IndoNanoT5-base](https://huggingface.co/LazarusNLP/IndoNanoT5-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6973
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- Rouge1: 0.6972
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- Rouge2: 0.0
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- Rougel: 0.6971
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- Rougelsum: 0.6984
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- Gen Len: 1.0
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.001
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- train_batch_size: 16
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- eval_batch_size: 32
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
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| 1.21 | 1.0 | 894 | 0.7570 | 0.6899 | 0.0 | 0.6953 | 0.6878 | 1.0 |
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| 0.6826 | 2.0 | 1788 | 0.6250 | 0.6779 | 0.0 | 0.6777 | 0.6768 | 1.0 |
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| 0.4899 | 3.0 | 2682 | 0.5915 | 0.6825 | 0.0 | 0.681 | 0.6837 | 1.0 |
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| 0.3413 | 4.0 | 3576 | 0.6194 | 0.7341 | 0.0 | 0.7341 | 0.7373 | 1.0 |
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| 0.2044 | 5.0 | 4470 | 0.6973 | 0.6972 | 0.0 | 0.6971 | 0.6984 | 1.0 |
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### Framework versions
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- Transformers 4.40.2
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- Pytorch 2.3.1+cu121
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- Datasets 2.20.0
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- Tokenizers 0.19.1
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