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AptaArkana
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indonesian-brand-indoBERT-finetuned

Text Classification
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bert
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  1. README.md +17 -12
  2. model.safetensors +1 -1
  3. runs/Mar14_04-37-38_0aee11b53b99/events.out.tfevents.1710391059.0aee11b53b99.275.0 +2 -2
  4. runs/Mar14_04-37-38_0aee11b53b99/events.out.tfevents.1710396388.0aee11b53b99.275.1 +3 -0
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 [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4266
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- - Accuracy: 0.8593
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- - Precision: 0.8593
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- - Recall: 0.8593
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- - F1: 0.8593
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  ## Model description
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@@ -50,22 +50,27 @@ The following hyperparameters were used during training:
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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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  - lr_scheduler_warmup_ratio: 0.01
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- - num_epochs: 5
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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- | No log | 1.0 | 304 | 0.4740 | 0.8123 | 0.8123 | 0.8123 | 0.8123 |
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- | 0.5873 | 2.0 | 608 | 0.4006 | 0.8551 | 0.8551 | 0.8551 | 0.8551 |
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- | 0.5873 | 3.0 | 912 | 0.4582 | 0.8444 | 0.8444 | 0.8444 | 0.8444 |
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- | 0.314 | 4.0 | 1216 | 0.4116 | 0.8576 | 0.8576 | 0.8576 | 0.8576 |
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- | 0.2177 | 5.0 | 1520 | 0.4266 | 0.8593 | 0.8593 | 0.8593 | 0.8593 |
 
 
 
 
 
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  ### Framework versions
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  - Transformers 4.38.2
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- - Pytorch 2.1.0+cu121
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  - Datasets 2.18.0
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  - Tokenizers 0.15.2
 
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  This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6848
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+ - Accuracy: 0.8601
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+ - Precision: 0.8601
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+ - Recall: 0.8601
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+ - F1: 0.8601
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  ## Model description
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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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  - lr_scheduler_warmup_ratio: 0.01
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+ - num_epochs: 10
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | No log | 1.0 | 304 | 0.4935 | 0.8132 | 0.8132 | 0.8132 | 0.8132 |
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+ | 0.5911 | 2.0 | 608 | 0.4046 | 0.8362 | 0.8362 | 0.8362 | 0.8362 |
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+ | 0.5911 | 3.0 | 912 | 0.4873 | 0.8305 | 0.8305 | 0.8305 | 0.8305 |
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+ | 0.3204 | 4.0 | 1216 | 0.4774 | 0.8560 | 0.8560 | 0.8560 | 0.8560 |
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+ | 0.2154 | 5.0 | 1520 | 0.5759 | 0.8486 | 0.8486 | 0.8486 | 0.8486 |
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+ | 0.2154 | 6.0 | 1824 | 0.6334 | 0.8568 | 0.8568 | 0.8568 | 0.8568 |
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+ | 0.1454 | 7.0 | 2128 | 0.6848 | 0.8601 | 0.8601 | 0.8601 | 0.8601 |
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+ | 0.1454 | 8.0 | 2432 | 0.7325 | 0.8560 | 0.8560 | 0.8560 | 0.8560 |
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+ | 0.0982 | 9.0 | 2736 | 0.7782 | 0.8568 | 0.8568 | 0.8568 | 0.8568 |
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+ | 0.0729 | 10.0 | 3040 | 0.7979 | 0.8584 | 0.8584 | 0.8584 | 0.8584 |
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  ### Framework versions
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  - Transformers 4.38.2
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+ - Pytorch 2.2.1+cu121
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  - Datasets 2.18.0
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  - Tokenizers 0.15.2
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