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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: 0.1910
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- - Accuracy: 0.9388
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- - F1: 0.8235
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- - Precision: 0.875
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- - Recall: 0.7778
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  ## Model description
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@@ -49,22 +49,14 @@ 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 | 25 | 0.3591 | 0.8571 | 0.3636 | 1.0 | 0.2222 |
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- | No log | 2.0 | 50 | 0.2682 | 0.8367 | 0.6667 | 0.5333 | 0.8889 |
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- | No log | 3.0 | 75 | 0.3667 | 0.8367 | 0.6667 | 0.5333 | 0.8889 |
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- | No log | 4.0 | 100 | 0.1910 | 0.9388 | 0.8235 | 0.875 | 0.7778 |
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- | No log | 5.0 | 125 | 0.3270 | 0.9184 | 0.7778 | 0.7778 | 0.7778 |
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- | No log | 6.0 | 150 | 0.3177 | 0.9184 | 0.8000 | 0.7273 | 0.8889 |
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- | No log | 7.0 | 175 | 0.3404 | 0.9184 | 0.7778 | 0.7778 | 0.7778 |
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- | No log | 8.0 | 200 | 0.3453 | 0.9184 | 0.7778 | 0.7778 | 0.7778 |
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- | No log | 9.0 | 225 | 0.3460 | 0.9184 | 0.7778 | 0.7778 | 0.7778 |
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- | No log | 10.0 | 250 | 0.3443 | 0.9184 | 0.7778 | 0.7778 | 0.7778 |
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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: 0.1965
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+ - Accuracy: 0.8980
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+ - F1: 0.8580
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+ - Precision: 0.8214
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+ - Recall: 0.9375
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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 | 2.0 | 50 | 0.4495 | 0.7755 | 0.7306 | 0.725 | 0.8625 |
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+ | No log | 4.0 | 100 | 0.2591 | 0.8980 | 0.8580 | 0.8214 | 0.9375 |
 
 
 
 
 
 
 
 
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  ### Framework versions
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