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Dhanang
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koneksi_model

Text Classification
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bert
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End of training

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  1. README.md +15 -16
  2. model.safetensors +1 -1
  3. runs/Jan14_09-58-33_fcd99226172a/events.out.tfevents.1705226316.fcd99226172a.370.8 +3 -0
  4. runs/Jan14_09-58-33_fcd99226172a/events.out.tfevents.1705226449.fcd99226172a.370.9 +3 -0
  5. training_args.bin +2 -2
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: 0.4885
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- - Accuracy: 0.8177
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- - F1: 0.8087
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- - Precision: 0.8916
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- - Recall: 0.74
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  ## Model description
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@@ -49,22 +49,21 @@ 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 | 96 | 0.4936 | 0.7760 | 0.7817 | 0.7938 | 0.77 |
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- | No log | 2.0 | 192 | 0.4885 | 0.8177 | 0.8087 | 0.8916 | 0.74 |
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- | No log | 3.0 | 288 | 0.6119 | 0.7552 | 0.7662 | 0.7624 | 0.77 |
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- | No log | 4.0 | 384 | 1.0256 | 0.7552 | 0.7314 | 0.8533 | 0.64 |
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- | No log | 5.0 | 480 | 1.2790 | 0.7604 | 0.7629 | 0.7872 | 0.74 |
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- | 0.2515 | 6.0 | 576 | 1.3453 | 0.7656 | 0.7716 | 0.7835 | 0.76 |
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- | 0.2515 | 7.0 | 672 | 1.4966 | 0.7708 | 0.7864 | 0.7642 | 0.81 |
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- | 0.2515 | 8.0 | 768 | 1.4197 | 0.7708 | 0.7660 | 0.8182 | 0.72 |
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- | 0.2515 | 9.0 | 864 | 1.5297 | 0.7760 | 0.7861 | 0.7822 | 0.79 |
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- | 0.2515 | 10.0 | 960 | 1.5265 | 0.7708 | 0.78 | 0.78 | 0.78 |
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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: 1.0917
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+ - Accuracy: 0.75
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+ - F1: 0.7493
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+ - Precision: 0.7497
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+ - Recall: 0.7491
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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 | 0.52 | 50 | 0.5014 | 0.7812 | 0.7810 | 0.7865 | 0.7839 |
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+ | No log | 1.04 | 100 | 0.5135 | 0.7708 | 0.7708 | 0.7732 | 0.7726 |
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+ | No log | 1.56 | 150 | 0.5564 | 0.7552 | 0.7503 | 0.7924 | 0.7624 |
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+ | No log | 2.08 | 200 | 0.5628 | 0.7604 | 0.7572 | 0.7659 | 0.7570 |
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+ | No log | 2.6 | 250 | 0.8524 | 0.7083 | 0.7037 | 0.7132 | 0.7043 |
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+ | No log | 3.12 | 300 | 0.6830 | 0.7448 | 0.7432 | 0.7456 | 0.7428 |
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+ | No log | 3.65 | 350 | 0.9662 | 0.7292 | 0.7262 | 0.7321 | 0.7261 |
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+ | No log | 4.17 | 400 | 0.9936 | 0.7656 | 0.7656 | 0.7659 | 0.7663 |
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+ | No log | 4.69 | 450 | 1.0558 | 0.7604 | 0.7603 | 0.7604 | 0.7609 |
 
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  ### Framework versions
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