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--- |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: ijelid-bert-base-multilingual |
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results: [] |
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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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# ijelid-bert-base-multilingual |
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This model is a fine-tuned version of [BERT multilingual base model (cased)](https://huggingface.co/bert-base-multilingual-cased) on the Indonesian-Javanese-English code-mixed Twitter dataset. |
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Label ID and its corresponding name: |
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| Label ID | Label Name | |
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|:---------------:|:------------------------------------------: |
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| LABEL_0 | English (EN) | |
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| LABEL_1 | Indonesian (ID) | |
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| LABEL_2 | Javanese (JV) | |
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| LABEL_3 | Mixed Indonesian-English (MIX-ID-EN) | |
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| LABEL_4 | Mixed Indonesian-Javanese (MIX-ID-JV) | |
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| LABEL_5 | Mixed Javanese-English (MIX-JV-EN) | |
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| LABEL_6 | Other (O) | |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3553 |
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- Precision: 0.9189 |
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- Recall: 0.9188 |
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- F1: 0.9187 |
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- Accuracy: 0.9451 |
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It achieves the following results on the test set: |
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- Overall Precision: 0.9249 |
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- Overall Recall: 0.9251 |
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- Overall F1: 0.925 |
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- Overall Accuracy: 0.951 |
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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: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| No log | 1.0 | 386 | 0.2340 | 0.8956 | 0.8507 | 0.8715 | 0.9239 | |
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| 0.3379 | 2.0 | 772 | 0.2101 | 0.9057 | 0.8904 | 0.8962 | 0.9342 | |
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| 0.1603 | 3.0 | 1158 | 0.2231 | 0.9252 | 0.8896 | 0.9065 | 0.9367 | |
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| 0.1079 | 4.0 | 1544 | 0.2013 | 0.9272 | 0.8902 | 0.9070 | 0.9420 | |
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| 0.1079 | 5.0 | 1930 | 0.2179 | 0.9031 | 0.9179 | 0.9103 | 0.9425 | |
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| 0.0701 | 6.0 | 2316 | 0.2330 | 0.9075 | 0.9165 | 0.9114 | 0.9435 | |
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| 0.051 | 7.0 | 2702 | 0.2433 | 0.9117 | 0.9190 | 0.9150 | 0.9432 | |
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| 0.0384 | 8.0 | 3088 | 0.2545 | 0.9001 | 0.9167 | 0.9078 | 0.9439 | |
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| 0.0384 | 9.0 | 3474 | 0.2629 | 0.9164 | 0.9159 | 0.9158 | 0.9444 | |
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| 0.0293 | 10.0 | 3860 | 0.2881 | 0.9263 | 0.9096 | 0.9178 | 0.9427 | |
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| 0.022 | 11.0 | 4246 | 0.2882 | 0.9167 | 0.9222 | 0.9191 | 0.9450 | |
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| 0.0171 | 12.0 | 4632 | 0.3028 | 0.9203 | 0.9152 | 0.9177 | 0.9447 | |
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| 0.0143 | 13.0 | 5018 | 0.3236 | 0.9155 | 0.9167 | 0.9158 | 0.9440 | |
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| 0.0143 | 14.0 | 5404 | 0.3301 | 0.9237 | 0.9163 | 0.9199 | 0.9444 | |
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| 0.0109 | 15.0 | 5790 | 0.3290 | 0.9187 | 0.9154 | 0.9169 | 0.9442 | |
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| 0.0092 | 16.0 | 6176 | 0.3308 | 0.9213 | 0.9178 | 0.9194 | 0.9448 | |
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| 0.0075 | 17.0 | 6562 | 0.3501 | 0.9273 | 0.9142 | 0.9206 | 0.9445 | |
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| 0.0075 | 18.0 | 6948 | 0.3520 | 0.9200 | 0.9184 | 0.9190 | 0.9447 | |
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| 0.0062 | 19.0 | 7334 | 0.3524 | 0.9238 | 0.9183 | 0.9210 | 0.9458 | |
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| 0.0051 | 20.0 | 7720 | 0.3553 | 0.9189 | 0.9188 | 0.9187 | 0.9451 | |
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### Framework versions |
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- Transformers 4.21.2 |
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- Pytorch 1.7.1 |
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- Datasets 2.5.1 |
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- Tokenizers 0.12.1 |
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