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--- |
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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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model-index: |
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- name: roberta-base-indonesian-1.5G-finetuned-wnli |
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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: 0.9246031746031746 |
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language: id |
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widget: |
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- text: "Saya mengapresiasi usaha anda" |
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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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# roberta-base-indonesian-1.5G-finetuned-wnli |
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This model is a fine-tuned version of [cahya/roberta-base-indonesian-1.5G](https://huggingface.co/cahya/roberta-base-indonesian-1.5G) on the indonlu dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5420 |
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- Accuracy: 0.9246 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 0.3123 | 1.0 | 688 | 0.3496 | 0.8944 | |
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| 0.1888 | 2.0 | 1376 | 0.2877 | 0.9103 | |
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| 0.0981 | 3.0 | 2064 | 0.3936 | 0.9143 | |
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| 0.0529 | 4.0 | 2752 | 0.4431 | 0.9183 | |
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| 0.0419 | 5.0 | 3440 | 0.5350 | 0.9167 | |
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| 0.0121 | 6.0 | 4128 | 0.5420 | 0.9246 | |
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| 0.0116 | 7.0 | 4816 | 0.5920 | 0.9175 | |
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| 0.0042 | 8.0 | 5504 | 0.6440 | 0.9190 | |
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| 0.0013 | 9.0 | 6192 | 0.6460 | 0.9222 | |
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| 0.001 | 10.0 | 6880 | 0.6575 | 0.9230 | |
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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 1.16.1 |
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- Tokenizers 0.10.3 |
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