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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-seq_bn-rf16 |
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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: 27.6391 |
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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-seq_bn-rf16 |
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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: 2.7479 |
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- Rouge1: 27.6391 |
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- Rouge2: 12.5407 |
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- Rougel: 23.5774 |
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- Rougelsum: 25.3376 |
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- Gen Len: 39.933 |
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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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| 2.6241 | 1.0 | 63 | 2.7534 | 23.3287 | 9.5988 | 20.1923 | 21.2916 | 33.387 | |
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| 2.228 | 2.0 | 126 | 2.7025 | 25.8033 | 10.8168 | 21.9451 | 23.4491 | 32.153 | |
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| 2.0615 | 3.0 | 189 | 2.6749 | 25.8887 | 10.7586 | 22.113 | 23.8997 | 30.873 | |
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| 1.9099 | 4.0 | 252 | 2.7197 | 26.5565 | 11.2255 | 22.6026 | 24.5495 | 31.524 | |
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| 1.8007 | 5.0 | 315 | 2.7479 | 26.9743 | 11.4843 | 22.9863 | 24.9284 | 33.854 | |
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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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