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--- |
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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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model-index: |
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- name: bert2bert-extreme-dropout-0.5-lr-5e-05-batchsize-4-encmaxlen-2048-decmaxlen-512 |
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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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# bert2bert-extreme-dropout-0.5-lr-5e-05-batchsize-4-encmaxlen-2048-decmaxlen-512 |
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This model was trained from scratch on the id_liputan6 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 8.6177 |
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- R1 Precision: 0.0188 |
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- R1 Recall: 0.0105 |
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- R1 Fmeasure: 0.0133 |
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- R2 Precision: 0.0 |
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- R2 Recall: 0.0 |
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- R2 Fmeasure: 0.0 |
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- Rl Precision: 0.0188 |
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- Rl Recall: 0.0105 |
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- Rl Fmeasure: 0.0133 |
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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: 5e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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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 |
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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 | R1 Precision | R1 Recall | R1 Fmeasure | R2 Precision | R2 Recall | R2 Fmeasure | Rl Precision | Rl Recall | Rl Fmeasure | |
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|:-------------:|:-----:|:------:|:---------------:|:------------:|:---------:|:-----------:|:------------:|:---------:|:-----------:|:------------:|:---------:|:-----------:| |
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| 7.0769 | 1.0 | 96942 | 7.5336 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 7.1014 | 2.0 | 193884 | 7.6800 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 7.0648 | 3.0 | 290826 | 8.1448 | 0.0188 | 0.0105 | 0.0133 | 0.0 | 0.0 | 0.0 | 0.0188 | 0.0105 | 0.0133 | |
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| 7.0594 | 4.0 | 387768 | 8.4518 | 0.0188 | 0.0105 | 0.0133 | 0.0 | 0.0 | 0.0 | 0.0188 | 0.0105 | 0.0133 | |
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| 7.0322 | 5.0 | 484710 | 8.6177 | 0.0188 | 0.0105 | 0.0133 | 0.0 | 0.0 | 0.0 | 0.0188 | 0.0105 | 0.0133 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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