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--- |
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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: pegasus-newsroom-malay_headlines |
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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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# pegasus-newsroom-malay_headlines |
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This model is a fine-tuned version of [google/pegasus-newsroom](https://huggingface.co./google/pegasus-newsroom) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6603 |
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- Rouge1: 42.6667 |
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- Rouge2: 22.8739 |
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- Rougel: 38.6684 |
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- Rougelsum: 38.6928 |
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- Gen Len: 34.7995 |
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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: 4 |
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- eval_batch_size: 4 |
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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: 3 |
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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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| 1.9713 | 1.0 | 15310 | 1.8121 | 41.1469 | 21.5262 | 37.3081 | 37.3377 | 35.0939 | |
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| 1.7917 | 2.0 | 30620 | 1.6913 | 42.4027 | 22.6089 | 38.4471 | 38.4699 | 34.8149 | |
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| 1.7271 | 3.0 | 45930 | 1.6603 | 42.6667 | 22.8739 | 38.6684 | 38.6928 | 34.7995 | |
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### Framework versions |
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- Transformers 4.12.2 |
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- Pytorch 1.9.0+cu111 |
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- Datasets 1.14.0 |
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- Tokenizers 0.10.3 |
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