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--- |
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tags: |
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- generated_from_trainer |
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datasets: |
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- indosum |
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metrics: |
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- rouge |
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model-index: |
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- name: t5-base-indonesian-summarization-cased-finetuned-indosum |
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results: |
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- task: |
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name: Sequence-to-sequence Language Modeling |
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type: text2text-generation |
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dataset: |
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name: indosum |
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type: indosum |
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config: indosum_fold0_source |
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split: validation |
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args: indosum_fold0_source |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 0.3278 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# t5-base-indonesian-summarization-cased-finetuned-indosum |
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This model is a fine-tuned version of [panggi/t5-base-indonesian-summarization-cased](https://huggingface.co/panggi/t5-base-indonesian-summarization-cased) on the indosum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5884 |
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- Rouge1: 0.3278 |
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- Rouge2: 0.2868 |
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- Rougel: 0.32 |
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- Rougelsum: 0.3198 |
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- Gen Len: 19.0 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5.6e-05 |
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- train_batch_size: 3 |
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- eval_batch_size: 3 |
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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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- num_epochs: 2 |
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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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| 0.3815 | 1.0 | 4754 | 0.5584 | 0.3281 | 0.2866 | 0.3202 | 0.32 | 19.0 | |
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| 0.3207 | 2.0 | 9508 | 0.5884 | 0.3278 | 0.2868 | 0.32 | 0.3198 | 19.0 | |
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### Framework versions |
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- Transformers 4.28.1 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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