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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: 44.408 |
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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: 0.2554 |
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- Rouge1: 44.408 |
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- Rouge2: 35.788 |
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- Rougel: 40.8449 |
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- Rougelsum: 43.0054 |
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- Gen Len: 62.247 |
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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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| 0.9013 | 1.0 | 63 | 0.3600 | 40.5674 | 32.5892 | 37.7471 | 39.1368 | 46.887 | |
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| 0.4754 | 2.0 | 126 | 0.2958 | 43.3031 | 34.5149 | 39.7514 | 41.863 | 56.767 | |
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| 0.3811 | 3.0 | 189 | 0.2629 | 43.4511 | 34.6775 | 39.9831 | 42.0606 | 57.898 | |
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| 0.3317 | 4.0 | 252 | 0.2610 | 43.9259 | 35.2198 | 40.3143 | 42.5364 | 57.815 | |
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| 0.299 | 5.0 | 315 | 0.2554 | 44.3826 | 35.7034 | 40.7597 | 42.9985 | 58.818 | |
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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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