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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-lora-8 |
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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: 44.041 |
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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-lora-8 |
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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: 0.2482 |
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- Rouge1: 44.041 |
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- Rouge2: 35.4021 |
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- Rougel: 40.435 |
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- Rougelsum: 42.6248 |
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- Gen Len: 60.602 |
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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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| 1.4611 | 1.0 | 63 | 0.4168 | 20.2294 | 15.1672 | 18.3462 | 19.5551 | 26.342 | |
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| 0.6123 | 2.0 | 126 | 0.3030 | 42.4943 | 33.9837 | 39.042 | 40.9843 | 54.709 | |
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| 0.4836 | 3.0 | 189 | 0.2516 | 39.2983 | 30.3972 | 36.1696 | 37.7681 | 48.258 | |
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| 0.4256 | 4.0 | 252 | 0.2482 | 42.8202 | 33.9496 | 39.2137 | 41.343 | 54.56 | |
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| 0.4014 | 5.0 | 315 | 0.2389 | 42.5107 | 33.6017 | 39.0118 | 41.0601 | 55.005 | |
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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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