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--- |
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license: mit |
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base_model: indolem/indobert-base-uncased |
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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: Zidan_model_output_v2 |
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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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# Zidan_model_output_v2 |
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This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co./indolem/indobert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7630 |
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- Accuracy: 0.6818 |
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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: 1e-06 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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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: 15 |
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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 | 220 | 1.0479 | 0.5091 | |
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| No log | 2.0 | 440 | 0.9568 | 0.5455 | |
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| 1.0321 | 3.0 | 660 | 0.9094 | 0.5818 | |
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| 1.0321 | 4.0 | 880 | 0.8748 | 0.6182 | |
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| 0.8487 | 5.0 | 1100 | 0.8410 | 0.6182 | |
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| 0.8487 | 6.0 | 1320 | 0.8203 | 0.6727 | |
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| 0.7405 | 7.0 | 1540 | 0.8106 | 0.6273 | |
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| 0.7405 | 8.0 | 1760 | 0.7971 | 0.6636 | |
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| 0.7405 | 9.0 | 1980 | 0.7852 | 0.6636 | |
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| 0.6747 | 10.0 | 2200 | 0.7788 | 0.6636 | |
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| 0.6747 | 11.0 | 2420 | 0.7754 | 0.6455 | |
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| 0.6304 | 12.0 | 2640 | 0.7688 | 0.6545 | |
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| 0.6304 | 13.0 | 2860 | 0.7656 | 0.6727 | |
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| 0.6064 | 14.0 | 3080 | 0.7626 | 0.6727 | |
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| 0.6064 | 15.0 | 3300 | 0.7630 | 0.6818 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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