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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-indobertweet |
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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-indobertweet |
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This model is a fine-tuned version of [indolem/indobertweet-base-uncased](https://huggingface.co/indolem/indobertweet-base-uncased) 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: 0.2804 |
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- Precision: 0.9323 |
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- Recall: 0.9394 |
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- F1: 0.9356 |
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- Accuracy: 0.9587 |
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It achieves the following results on the test set: |
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- Overall Precision: 0.9326 |
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- Overall Recall: 0.9421 |
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- Overall F1: 0.9371 |
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- Overall Accuracy: 0.9643 |
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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 | 0.1666 | 0.8968 | 0.9014 | 0.8982 | 0.9465 | |
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| 0.257 | 2.0 | 772 | 0.1522 | 0.9062 | 0.9368 | 0.9206 | 0.9517 | |
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| 0.1092 | 3.0 | 1158 | 0.1462 | 0.9233 | 0.9335 | 0.9280 | 0.9556 | |
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| 0.0739 | 4.0 | 1544 | 0.1563 | 0.9312 | 0.9361 | 0.9336 | 0.9568 | |
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| 0.0739 | 5.0 | 1930 | 0.1671 | 0.9224 | 0.9413 | 0.9312 | 0.9573 | |
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| 0.0474 | 6.0 | 2316 | 0.1719 | 0.9303 | 0.9394 | 0.9346 | 0.9578 | |
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| 0.0339 | 7.0 | 2702 | 0.1841 | 0.9249 | 0.9389 | 0.9314 | 0.9576 | |
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| 0.0237 | 8.0 | 3088 | 0.2030 | 0.9224 | 0.9380 | 0.9297 | 0.9570 | |
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| 0.0237 | 9.0 | 3474 | 0.2106 | 0.9289 | 0.9377 | 0.9331 | 0.9576 | |
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| 0.0185 | 10.0 | 3860 | 0.2264 | 0.9277 | 0.9389 | 0.9330 | 0.9571 | |
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| 0.0132 | 11.0 | 4246 | 0.2331 | 0.9336 | 0.9344 | 0.9339 | 0.9574 | |
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| 0.0101 | 12.0 | 4632 | 0.2403 | 0.9353 | 0.9375 | 0.9363 | 0.9586 | |
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| 0.0082 | 13.0 | 5018 | 0.2509 | 0.9311 | 0.9373 | 0.9340 | 0.9582 | |
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| 0.0082 | 14.0 | 5404 | 0.2548 | 0.9344 | 0.9351 | 0.9346 | 0.9578 | |
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| 0.0062 | 15.0 | 5790 | 0.2608 | 0.9359 | 0.9372 | 0.9365 | 0.9588 | |
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| 0.005 | 16.0 | 6176 | 0.2667 | 0.9298 | 0.9407 | 0.9350 | 0.9587 | |
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| 0.0045 | 17.0 | 6562 | 0.2741 | 0.9337 | 0.9408 | 0.9371 | 0.9592 | |
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| 0.0045 | 18.0 | 6948 | 0.2793 | 0.9342 | 0.9371 | 0.9355 | 0.9589 | |
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| 0.0035 | 19.0 | 7334 | 0.2806 | 0.9299 | 0.9391 | 0.9342 | 0.9588 | |
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| 0.0034 | 20.0 | 7720 | 0.2804 | 0.9323 | 0.9394 | 0.9356 | 0.9587 | |
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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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