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--- |
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language: id |
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widget: |
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- text: Entah mengapa saya merasakan ada sesuatu yang janggal di produk ini |
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license: mit |
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tags: |
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- generated_from_trainer |
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datasets: |
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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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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: indonlu |
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type: indonlu |
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args: smsa |
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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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should probably proofread and complete it, then remove this comment. --> |
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# indobert-base-uncased-finetuned-indonlu-smsa |
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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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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-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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- 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 |
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- Transformers 4.14.1 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 1.17.0 |
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- Tokenizers 0.10.3 |
