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Dhanang
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gacha_model

Text Classification
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bert
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End of training

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  1. README.md +27 -16
  2. model.safetensors +1 -1
  3. runs/Jan14_09-39-45_fcd99226172a/events.out.tfevents.1705225186.fcd99226172a.370.4 +2 -2
  4. runs/Jan14_09-39-45_fcd99226172a/events.out.tfevents.1705225571.fcd99226172a.370.5 +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 [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: 0.4437
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- - Accuracy: 0.8065
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- - F1: 0.7877
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- - Precision: 0.8105
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- - Recall: 0.7662
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  ## Model description
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@@ -49,22 +49,33 @@ 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 | 215 | 0.4437 | 0.8065 | 0.7877 | 0.8105 | 0.7662 |
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- | No log | 2.0 | 430 | 0.4728 | 0.8042 | 0.7766 | 0.8343 | 0.7264 |
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- | 0.343 | 3.0 | 645 | 0.7781 | 0.8089 | 0.7940 | 0.8020 | 0.7861 |
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- | 0.343 | 4.0 | 860 | 0.9427 | 0.8089 | 0.7842 | 0.8324 | 0.7413 |
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- | 0.0974 | 5.0 | 1075 | 1.1330 | 0.8089 | 0.7807 | 0.8439 | 0.7264 |
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- | 0.0974 | 6.0 | 1290 | 1.2451 | 0.8019 | 0.7781 | 0.8187 | 0.7413 |
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- | 0.0187 | 7.0 | 1505 | 1.2750 | 0.8205 | 0.7958 | 0.8523 | 0.7463 |
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- | 0.0187 | 8.0 | 1720 | 1.3551 | 0.8135 | 0.7849 | 0.8538 | 0.7264 |
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- | 0.0187 | 9.0 | 1935 | 1.3652 | 0.8205 | 0.7979 | 0.8444 | 0.7562 |
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- | 0.0018 | 10.0 | 2150 | 1.4262 | 0.8112 | 0.7817 | 0.8529 | 0.7214 |
 
 
 
 
 
 
 
 
 
 
 
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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: 0.5789
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+ - Accuracy: 0.8089
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+ - F1: 0.8065
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+ - Precision: 0.8115
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+ - Recall: 0.8052
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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 | 0.23 | 50 | 0.5084 | 0.7739 | 0.7737 | 0.7826 | 0.7790 |
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+ | No log | 0.47 | 100 | 0.4663 | 0.7972 | 0.7967 | 0.7964 | 0.7971 |
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+ | No log | 0.7 | 150 | 0.4834 | 0.8112 | 0.8094 | 0.8125 | 0.8082 |
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+ | No log | 0.93 | 200 | 0.4445 | 0.8135 | 0.8104 | 0.8194 | 0.8087 |
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+ | No log | 1.16 | 250 | 0.6506 | 0.7879 | 0.7786 | 0.8149 | 0.7781 |
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+ | No log | 1.4 | 300 | 0.5314 | 0.7692 | 0.7687 | 0.7810 | 0.7752 |
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+ | No log | 1.63 | 350 | 0.5149 | 0.8065 | 0.8021 | 0.8167 | 0.8003 |
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+ | No log | 1.86 | 400 | 0.4735 | 0.8298 | 0.8289 | 0.8296 | 0.8284 |
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+ | No log | 2.09 | 450 | 0.5093 | 0.8275 | 0.8262 | 0.8280 | 0.8253 |
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+ | 0.3338 | 2.33 | 500 | 0.5789 | 0.8089 | 0.8065 | 0.8115 | 0.8052 |
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+ | 0.3338 | 2.56 | 550 | 0.6539 | 0.8065 | 0.8059 | 0.8057 | 0.8062 |
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+ | 0.3338 | 2.79 | 600 | 0.6995 | 0.8042 | 0.8018 | 0.8068 | 0.8005 |
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+ | 0.3338 | 3.02 | 650 | 0.8298 | 0.8182 | 0.8168 | 0.8186 | 0.8160 |
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+ | 0.3338 | 3.26 | 700 | 0.7829 | 0.8089 | 0.8077 | 0.8085 | 0.8072 |
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+ | 0.3338 | 3.49 | 750 | 0.7700 | 0.8205 | 0.8195 | 0.8202 | 0.8191 |
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+ | 0.3338 | 3.72 | 800 | 0.9060 | 0.8089 | 0.8057 | 0.8145 | 0.8040 |
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+ | 0.3338 | 3.95 | 850 | 0.9478 | 0.8112 | 0.8072 | 0.8205 | 0.8053 |
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+ | 0.3338 | 4.19 | 900 | 0.9171 | 0.8089 | 0.8067 | 0.8109 | 0.8054 |
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+ | 0.3338 | 4.42 | 950 | 0.9512 | 0.8065 | 0.8043 | 0.8088 | 0.8030 |
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+ | 0.079 | 4.65 | 1000 | 0.9579 | 0.8065 | 0.8047 | 0.8078 | 0.8035 |
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+ | 0.079 | 4.88 | 1050 | 0.9471 | 0.8089 | 0.8073 | 0.8095 | 0.8063 |
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  ### Framework versions
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