Dhanang commited on
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0307753
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End of training

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README.md CHANGED
@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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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: 0.3276
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- - Accuracy: 0.8701
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- - F1: 0.8832
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- - Precision: 0.87
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- - Recall: 0.8969
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  ## Model description
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@@ -49,22 +49,20 @@ The following hyperparameters were used during training:
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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: 10
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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 | 1.0 | 89 | 0.3276 | 0.8701 | 0.8832 | 0.87 | 0.8969 |
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- | No log | 2.0 | 178 | 0.3607 | 0.8588 | 0.8744 | 0.8529 | 0.8969 |
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- | No log | 3.0 | 267 | 0.4801 | 0.8870 | 0.9 | 0.8738 | 0.9278 |
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- | No log | 4.0 | 356 | 0.5740 | 0.8870 | 0.8990 | 0.8812 | 0.9175 |
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- | No log | 5.0 | 445 | 0.5676 | 0.9040 | 0.9119 | 0.9167 | 0.9072 |
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- | 0.1393 | 6.0 | 534 | 0.6471 | 0.9040 | 0.9128 | 0.9082 | 0.9175 |
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- | 0.1393 | 7.0 | 623 | 0.6998 | 0.8870 | 0.8990 | 0.8812 | 0.9175 |
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- | 0.1393 | 8.0 | 712 | 0.7484 | 0.8870 | 0.8990 | 0.8812 | 0.9175 |
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- | 0.1393 | 9.0 | 801 | 0.7502 | 0.8870 | 0.8990 | 0.8812 | 0.9175 |
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- | 0.1393 | 10.0 | 890 | 0.7642 | 0.8870 | 0.8990 | 0.8812 | 0.9175 |
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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: 0.6126
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+ - Accuracy: 0.8927
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+ - F1: 0.8906
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+ - Precision: 0.8964
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+ - Recall: 0.8878
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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 | 0.56 | 50 | 0.3455 | 0.8757 | 0.8736 | 0.8780 | 0.8713 |
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+ | No log | 1.12 | 100 | 0.3013 | 0.8701 | 0.8687 | 0.8692 | 0.8683 |
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+ | No log | 1.69 | 150 | 0.3773 | 0.8644 | 0.8616 | 0.8683 | 0.8588 |
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+ | No log | 2.25 | 200 | 0.3923 | 0.8927 | 0.8906 | 0.8964 | 0.8878 |
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+ | No log | 2.81 | 250 | 0.3634 | 0.8927 | 0.8913 | 0.8931 | 0.8900 |
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+ | No log | 3.37 | 300 | 0.4554 | 0.8983 | 0.8971 | 0.8982 | 0.8963 |
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+ | No log | 3.93 | 350 | 0.5317 | 0.8870 | 0.8851 | 0.8896 | 0.8827 |
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+ | No log | 4.49 | 400 | 0.5834 | 0.8870 | 0.8851 | 0.8896 | 0.8827 |
 
 
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  ### Framework versions
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