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ayameRushia
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indobert-base-uncased-finetuned-indonlu-smsa

Text Classification
Transformers
PyTorch
Safetensors
Indonesian
bert
generated_from_trainer
Eval Results
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update model card README.md

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@@ -6,6 +6,9 @@ datasets:
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  - indonlu
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  metrics:
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  - accuracy
 
 
 
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  model-index:
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  - name: indobert-base-uncased-finetuned-indonlu-smsa
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  results:
@@ -19,7 +22,16 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.9365079365079365
 
 
 
 
 
 
 
 
 
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -29,8 +41,11 @@ 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 indonlu dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2416
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- - Accuracy: 0.9365
 
 
 
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  ## Model description
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@@ -55,23 +70,23 @@ 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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- - lr_scheduler_warmup_steps: 2000
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  - num_epochs: 10
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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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- | No log | 1.0 | 344 | 0.6655 | 0.7206 |
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- | 0.7832 | 2.0 | 688 | 0.3297 | 0.8651 |
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- | 0.3331 | 3.0 | 1032 | 0.2184 | 0.9254 |
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- | 0.3331 | 4.0 | 1376 | 0.2057 | 0.9302 |
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- | 0.2053 | 5.0 | 1720 | 0.2105 | 0.9270 |
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- | 0.1408 | 6.0 | 2064 | 0.2036 | 0.9270 |
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- | 0.1408 | 7.0 | 2408 | 0.2416 | 0.9365 |
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- | 0.1044 | 8.0 | 2752 | 0.3145 | 0.9302 |
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- | 0.0637 | 9.0 | 3096 | 0.3095 | 0.9294 |
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- | 0.0637 | 10.0 | 3440 | 0.3354 | 0.9286 |
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  ### Framework versions
 
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  - indonlu
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  metrics:
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  - accuracy
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+ - f1
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+ - precision
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+ - recall
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  model-index:
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  - name: indobert-base-uncased-finetuned-indonlu-smsa
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  results:
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9301587301587302
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+ - name: F1
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+ type: f1
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+ value: 0.9066105299178986
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+ - name: Precision
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+ type: precision
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+ value: 0.8992078788375845
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+ - name: Recall
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+ type: recall
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+ value: 0.9147307323234121
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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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 indonlu dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2277
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+ - Accuracy: 0.9302
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+ - F1: 0.9066
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+ - Precision: 0.8992
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+ - Recall: 0.9147
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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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+ - lr_scheduler_warmup_steps: 1500
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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 | 344 | 0.3831 | 0.8476 | 0.7715 | 0.7817 | 0.7627 |
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+ | 0.4167 | 2.0 | 688 | 0.2809 | 0.8905 | 0.8406 | 0.8699 | 0.8185 |
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+ | 0.2624 | 3.0 | 1032 | 0.2254 | 0.9230 | 0.8842 | 0.9004 | 0.8714 |
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+ | 0.2624 | 4.0 | 1376 | 0.2378 | 0.9238 | 0.8797 | 0.9180 | 0.8594 |
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+ | 0.1865 | 5.0 | 1720 | 0.2277 | 0.9302 | 0.9066 | 0.8992 | 0.9147 |
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+ | 0.1217 | 6.0 | 2064 | 0.2444 | 0.9262 | 0.8981 | 0.9013 | 0.8957 |
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+ | 0.1217 | 7.0 | 2408 | 0.2985 | 0.9286 | 0.8999 | 0.9035 | 0.8971 |
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+ | 0.0847 | 8.0 | 2752 | 0.3397 | 0.9278 | 0.8969 | 0.9090 | 0.8871 |
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+ | 0.0551 | 9.0 | 3096 | 0.3542 | 0.9270 | 0.8961 | 0.9010 | 0.8924 |
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+ | 0.0551 | 10.0 | 3440 | 0.3862 | 0.9222 | 0.8895 | 0.8970 | 0.8846 |
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  ### Framework versions