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--- |
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license: mit |
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base_model: w11wo/indo-roberta-small |
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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: indo-roberta-small-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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config: smsa |
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split: validation |
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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: 0.888095238095238 |
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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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# indo-roberta-small-finetuned-indonlu-smsa |
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This model is a fine-tuned version of [w11wo/indo-roberta-small](https://huggingface.co/w11wo/indo-roberta-small) on the indonlu dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4497 |
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- Accuracy: 0.8881 |
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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: 64 |
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- eval_batch_size: 64 |
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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: 1000 |
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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 | 172 | 0.6502 | 0.7143 | |
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| No log | 2.0 | 344 | 0.4720 | 0.8127 | |
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| 0.6168 | 3.0 | 516 | 0.4511 | 0.8357 | |
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| 0.6168 | 4.0 | 688 | 0.3825 | 0.8540 | |
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| 0.6168 | 5.0 | 860 | 0.3655 | 0.8595 | |
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| 0.2954 | 6.0 | 1032 | 0.3672 | 0.8683 | |
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| 0.2954 | 7.0 | 1204 | 0.3839 | 0.8746 | |
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| 0.2954 | 8.0 | 1376 | 0.4220 | 0.8706 | |
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| 0.1328 | 9.0 | 1548 | 0.4497 | 0.8881 | |
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| 0.1328 | 10.0 | 1720 | 0.4455 | 0.8865 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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