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text-classification

Text Classification
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End of training

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  1. README.md +20 -32
  2. model.safetensors +1 -1
  3. runs/Jun11_02-37-21_d8953cd469c0/events.out.tfevents.1718074706.d8953cd469c0.659.3 +3 -0
README.md CHANGED
@@ -1,10 +1,8 @@
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  ---
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  license: mit
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- base_model: indolem/indobert-base-uncased
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  tags:
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  - generated_from_trainer
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- metrics:
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- - accuracy
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  model-index:
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  - name: text-classification
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  results: []
@@ -15,10 +13,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # text-classification
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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: 0.9158
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- - Accuracy: 0.7695
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  ## Model description
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@@ -38,42 +36,32 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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- - train_batch_size: 8
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- - eval_batch_size: 8
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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: 20
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 1.0037 | 1.0 | 499 | 1.0119 | 0.7024 |
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- | 0.7645 | 2.0 | 998 | 0.9929 | 0.7275 |
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- | 0.6417 | 3.0 | 1497 | 0.9623 | 0.7335 |
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- | 0.8177 | 4.0 | 1996 | 0.9158 | 0.7695 |
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- | 0.4176 | 5.0 | 2495 | 1.2640 | 0.7635 |
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- | 0.7335 | 6.0 | 2994 | 1.2080 | 0.7615 |
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- | 0.3151 | 7.0 | 3493 | 1.3485 | 0.7575 |
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- | 0.7147 | 8.0 | 3992 | 1.2736 | 0.7605 |
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- | 0.0728 | 9.0 | 4491 | 1.4076 | 0.7565 |
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- | 0.2183 | 10.0 | 4990 | 1.5012 | 0.7505 |
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- | 0.2202 | 11.0 | 5489 | 1.5981 | 0.7405 |
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- | 0.2694 | 12.0 | 5988 | 1.5516 | 0.7415 |
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- | 0.0497 | 13.0 | 6487 | 1.6425 | 0.7485 |
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- | 0.2473 | 14.0 | 6986 | 1.7087 | 0.7475 |
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- | 0.1949 | 15.0 | 7485 | 1.6820 | 0.7535 |
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- | 0.1233 | 16.0 | 7984 | 1.7447 | 0.7405 |
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- | 0.0632 | 17.0 | 8483 | 1.7229 | 0.7475 |
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- | 0.1161 | 18.0 | 8982 | 1.7292 | 0.7545 |
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- | 0.0023 | 19.0 | 9481 | 1.7930 | 0.7465 |
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- | 0.0854 | 20.0 | 9980 | 1.8089 | 0.7495 |
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  ### Framework versions
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- - Transformers 4.41.1
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  - Pytorch 2.3.0+cu121
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  - Datasets 2.19.2
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  - Tokenizers 0.19.1
 
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  ---
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  license: mit
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+ base_model: indobenchmark/indobert-base-p1
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  tags:
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  - generated_from_trainer
 
 
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  model-index:
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  - name: text-classification
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  results: []
 
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  # text-classification
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+ This model is a fine-tuned version of [indobenchmark/indobert-base-p1](https://huggingface.co/indobenchmark/indobert-base-p1) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.4590
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+ - Balanced Accuracy: 0.6868
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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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 | Balanced Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:-----------------:|
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+ | No log | 1.0 | 125 | 0.4590 | 0.6868 |
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+ | No log | 2.0 | 250 | 0.5104 | 0.6470 |
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+ | No log | 3.0 | 375 | 0.5941 | 0.6448 |
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+ | 0.3146 | 4.0 | 500 | 0.5873 | 0.7828 |
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+ | 0.3146 | 5.0 | 625 | 0.6645 | 0.8005 |
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+ | 0.3146 | 6.0 | 750 | 0.6635 | 0.8110 |
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+ | 0.3146 | 7.0 | 875 | 0.6684 | 0.7801 |
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+ | 0.0956 | 8.0 | 1000 | 0.8031 | 0.7786 |
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+ | 0.0956 | 9.0 | 1125 | 0.7523 | 0.7827 |
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+ | 0.0956 | 10.0 | 1250 | 0.7878 | 0.7715 |
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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+ - Transformers 4.41.2
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  - Pytorch 2.3.0+cu121
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  - Datasets 2.19.2
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  - Tokenizers 0.19.1
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