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--- |
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license: apache-2.0 |
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base_model: cahya/bert2bert-indonesian-summarization |
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tags: |
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- generated_from_trainer |
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metrics: |
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- rouge |
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model-index: |
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- name: finetuning_summarization |
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results: [] |
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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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# finetuning_summarization |
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This model is a fine-tuned version of [cahya/bert2bert-indonesian-summarization](https://huggingface.co./cahya/bert2bert-indonesian-summarization) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6759 |
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- Rouge1: 0.8455 |
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- Rouge2: 0.742 |
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- Rougel: 0.8486 |
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- Rougelsum: 0.8475 |
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- Gen Len: 23.7368 |
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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: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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: 10 |
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- mixed_precision_training: Native AMP |
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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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| No log | 1.0 | 5 | 1.3699 | 0.8443 | 0.7258 | 0.8426 | 0.8435 | 25.8421 | |
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| No log | 2.0 | 10 | 1.0257 | 0.8282 | 0.7115 | 0.8293 | 0.8275 | 25.0 | |
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| No log | 3.0 | 15 | 0.7871 | 0.8384 | 0.7277 | 0.8397 | 0.8396 | 24.3158 | |
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| No log | 4.0 | 20 | 0.7078 | 0.8339 | 0.7318 | 0.8358 | 0.8348 | 23.4211 | |
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| No log | 5.0 | 25 | 0.6994 | 0.843 | 0.7396 | 0.8451 | 0.845 | 24.0 | |
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| No log | 6.0 | 30 | 0.6832 | 0.8445 | 0.7413 | 0.8419 | 0.842 | 23.4737 | |
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| No log | 7.0 | 35 | 0.6768 | 0.8429 | 0.742 | 0.8451 | 0.8448 | 23.6842 | |
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| No log | 8.0 | 40 | 0.6736 | 0.843 | 0.7396 | 0.8451 | 0.845 | 23.6842 | |
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| No log | 9.0 | 45 | 0.6750 | 0.843 | 0.7396 | 0.8451 | 0.845 | 23.6842 | |
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| No log | 10.0 | 50 | 0.6759 | 0.8455 | 0.742 | 0.8486 | 0.8475 | 23.7368 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.2.0+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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