End of training
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README.md
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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:
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- Accuracy: 0.
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- F1: 0.
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- Precision: 0.
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- Recall: 0.
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## Model description
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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:
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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| 0.1904 | 10.0 | 920 | 1.4867 | 0.8022 | 0.8732 | 0.8435 | 0.9051 |
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### Framework versions
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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: 1.3853
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- Accuracy: 0.7857
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- F1: 0.6904
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- Precision: 0.7095
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- Recall: 0.6786
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## Model description
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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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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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| No log | 0.54 | 50 | 0.6229 | 0.7582 | 0.6537 | 0.6671 | 0.6454 |
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| No log | 1.09 | 100 | 0.6750 | 0.7747 | 0.6557 | 0.6912 | 0.6414 |
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| No log | 1.63 | 150 | 0.5936 | 0.7802 | 0.7242 | 0.7137 | 0.7421 |
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| No log | 2.17 | 200 | 0.7087 | 0.7912 | 0.7312 | 0.7232 | 0.7419 |
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| No log | 2.72 | 250 | 0.9279 | 0.7802 | 0.6796 | 0.7007 | 0.6675 |
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| No log | 3.26 | 300 | 1.0408 | 0.7747 | 0.6853 | 0.6940 | 0.6788 |
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| No log | 3.8 | 350 | 1.2506 | 0.7857 | 0.7007 | 0.7100 | 0.6935 |
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| No log | 4.35 | 400 | 1.4011 | 0.7802 | 0.6796 | 0.7007 | 0.6675 |
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| No log | 4.89 | 450 | 1.3770 | 0.7857 | 0.6904 | 0.7095 | 0.6786 |
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### Framework versions
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model.safetensors
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