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--- |
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language: |
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- id |
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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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- generated_from_trainer |
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datasets: |
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- id_liputan6 |
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metrics: |
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- rouge |
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model-index: |
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- name: liputan6-pt-pl5 |
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results: |
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- task: |
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name: Summarization |
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type: summarization |
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dataset: |
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name: id_liputan6 canonical |
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type: id_liputan6 |
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config: canonical |
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split: validation |
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args: canonical |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 29.4984 |
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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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# liputan6-pt-pl5 |
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This model is a fine-tuned version of [LazarusNLP/IndoNanoT5-base](https://huggingface.co./LazarusNLP/IndoNanoT5-base) on the id_liputan6 canonical dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.7526 |
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- Rouge1: 29.4984 |
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- Rouge2: 14.2115 |
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- Rougel: 24.9259 |
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- Rougelsum: 27.5126 |
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- Gen Len: 59.201 |
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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: 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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- num_epochs: 5.0 |
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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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| 4.309 | 1.0 | 63 | 3.4072 | 20.861 | 8.8494 | 18.3118 | 19.3333 | 41.853 | |
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| 3.6184 | 2.0 | 126 | 3.1460 | 25.8149 | 9.9065 | 21.2242 | 23.6534 | 51.44 | |
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| 3.3773 | 3.0 | 189 | 2.9716 | 27.0263 | 11.563 | 22.6018 | 25.0075 | 55.215 | |
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| 3.1793 | 4.0 | 252 | 2.8266 | 28.6871 | 12.9802 | 24.038 | 26.6558 | 52.119 | |
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| 3.0027 | 5.0 | 315 | 2.7526 | 29.5518 | 13.5408 | 24.834 | 27.6096 | 51.956 | |
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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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