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Dhanang
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story_model

Text Classification
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bert
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End of training

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  1. README.md +14 -15
  2. model.safetensors +1 -1
  3. runs/Jan14_10-05-40_fcd99226172a/events.out.tfevents.1705226742.fcd99226172a.370.10 +3 -0
  4. runs/Jan14_10-05-40_fcd99226172a/events.out.tfevents.1705226881.fcd99226172a.370.11 +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: 0.2576
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  - Accuracy: 0.9409
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- - F1: 0.9622
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- - Precision: 0.9929
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- - Recall: 0.9333
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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 | 94 | 0.3243 | 0.8817 | 0.9308 | 0.8810 | 0.9867 |
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- | No log | 2.0 | 188 | 0.2781 | 0.8925 | 0.9363 | 0.8963 | 0.98 |
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- | No log | 3.0 | 282 | 0.2576 | 0.9409 | 0.9622 | 0.9929 | 0.9333 |
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- | No log | 4.0 | 376 | 0.3482 | 0.9247 | 0.9545 | 0.9304 | 0.98 |
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- | No log | 5.0 | 470 | 0.3785 | 0.9301 | 0.9574 | 0.9419 | 0.9733 |
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- | 0.1516 | 6.0 | 564 | 0.4252 | 0.9140 | 0.9467 | 0.9467 | 0.9467 |
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- | 0.1516 | 7.0 | 658 | 0.5097 | 0.9086 | 0.9428 | 0.9524 | 0.9333 |
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- | 0.1516 | 8.0 | 752 | 0.5036 | 0.9086 | 0.9431 | 0.9463 | 0.94 |
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- | 0.1516 | 9.0 | 846 | 0.5268 | 0.9086 | 0.9439 | 0.9346 | 0.9533 |
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- | 0.1516 | 10.0 | 940 | 0.5314 | 0.9086 | 0.9439 | 0.9346 | 0.9533 |
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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: 0.2923
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  - Accuracy: 0.9409
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+ - F1: 0.9043
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+ - Precision: 0.9087
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+ - Recall: 0.9
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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 | 0.53 | 50 | 0.5324 | 0.8978 | 0.8032 | 0.9009 | 0.7572 |
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+ | No log | 1.06 | 100 | 0.2795 | 0.9355 | 0.8967 | 0.8967 | 0.8967 |
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+ | No log | 1.6 | 150 | 0.2561 | 0.9194 | 0.8772 | 0.8608 | 0.8972 |
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+ | No log | 2.13 | 200 | 0.3274 | 0.9194 | 0.8635 | 0.8871 | 0.8444 |
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+ | No log | 2.66 | 250 | 0.2756 | 0.9247 | 0.8819 | 0.8745 | 0.89 |
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+ | No log | 3.19 | 300 | 0.4554 | 0.9032 | 0.8302 | 0.8696 | 0.8028 |
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+ | No log | 3.72 | 350 | 0.2333 | 0.9462 | 0.9157 | 0.9075 | 0.9244 |
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+ | No log | 4.26 | 400 | 0.4101 | 0.9247 | 0.8711 | 0.9013 | 0.8478 |
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+ | No log | 4.79 | 450 | 0.2826 | 0.9409 | 0.9063 | 0.9021 | 0.9106 |
 
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  ### Framework versions
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