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--- |
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license: mit |
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base_model: indobenchmark/indobert-base-p2 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: aspect_model |
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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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# aspect_model |
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This model is a fine-tuned version of [indobenchmark/indobert-base-p2](https://huggingface.co/indobenchmark/indobert-base-p2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3490 |
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- Accuracy: 0.8084 |
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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: 16 |
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- eval_batch_size: 16 |
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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: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| No log | 1.0 | 72 | 0.6516 | 0.7735 | |
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| No log | 2.0 | 144 | 0.6119 | 0.7909 | |
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| No log | 3.0 | 216 | 0.6152 | 0.8049 | |
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| No log | 4.0 | 288 | 0.7480 | 0.8118 | |
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| No log | 5.0 | 360 | 1.0121 | 0.7770 | |
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| No log | 6.0 | 432 | 1.0780 | 0.7909 | |
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| 0.27 | 7.0 | 504 | 1.1602 | 0.7840 | |
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| 0.27 | 8.0 | 576 | 1.2136 | 0.8014 | |
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| 0.27 | 9.0 | 648 | 1.2490 | 0.8014 | |
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| 0.27 | 10.0 | 720 | 1.3102 | 0.7840 | |
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| 0.27 | 11.0 | 792 | 1.3184 | 0.8049 | |
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| 0.27 | 12.0 | 864 | 1.3255 | 0.8014 | |
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| 0.27 | 13.0 | 936 | 1.3192 | 0.8049 | |
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| 0.0022 | 14.0 | 1008 | 1.3229 | 0.7944 | |
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| 0.0022 | 15.0 | 1080 | 1.3415 | 0.8014 | |
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| 0.0022 | 16.0 | 1152 | 1.3515 | 0.7909 | |
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| 0.0022 | 17.0 | 1224 | 1.3544 | 0.7944 | |
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| 0.0022 | 18.0 | 1296 | 1.3529 | 0.7944 | |
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| 0.0022 | 19.0 | 1368 | 1.3484 | 0.8084 | |
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| 0.0022 | 20.0 | 1440 | 1.3490 | 0.8084 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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