ijelid-indobertweet / README.md
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metadata
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: ijelid-indobertweet
    results: []

ijelid-indobertweet

This model is a fine-tuned version of indolem/indobertweet-base-uncased on the Indonesian-Javanese-English code-mixed Twitter dataset.

Label ID and its corresponding name:

Label ID Label Name
LABEL_0 English (EN)
LABEL_1 Indonesian (ID)
LABEL_2 Javanese (JV)
LABEL_3 Mixed Indonesian-English (MIX-ID-EN)
LABEL_4 Mixed Indonesian-Javanese (MIX-ID-JV)
LABEL_5 Mixed Javanese-English (MIX-JV-EN)
LABEL_6 Other (O)

It achieves the following results on the evaluation set:

  • Loss: 0.2804
  • Precision: 0.9323
  • Recall: 0.9394
  • F1: 0.9356
  • Accuracy: 0.9587

It achieves the following results on the test set:

  • Overall Precision: 0.9326
  • Overall Recall: 0.9421
  • Overall F1: 0.9371
  • Overall Accuracy: 0.9643

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 2e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 1.0 386 0.1666 0.8968 0.9014 0.8982 0.9465
0.257 2.0 772 0.1522 0.9062 0.9368 0.9206 0.9517
0.1092 3.0 1158 0.1462 0.9233 0.9335 0.9280 0.9556
0.0739 4.0 1544 0.1563 0.9312 0.9361 0.9336 0.9568
0.0739 5.0 1930 0.1671 0.9224 0.9413 0.9312 0.9573
0.0474 6.0 2316 0.1719 0.9303 0.9394 0.9346 0.9578
0.0339 7.0 2702 0.1841 0.9249 0.9389 0.9314 0.9576
0.0237 8.0 3088 0.2030 0.9224 0.9380 0.9297 0.9570
0.0237 9.0 3474 0.2106 0.9289 0.9377 0.9331 0.9576
0.0185 10.0 3860 0.2264 0.9277 0.9389 0.9330 0.9571
0.0132 11.0 4246 0.2331 0.9336 0.9344 0.9339 0.9574
0.0101 12.0 4632 0.2403 0.9353 0.9375 0.9363 0.9586
0.0082 13.0 5018 0.2509 0.9311 0.9373 0.9340 0.9582
0.0082 14.0 5404 0.2548 0.9344 0.9351 0.9346 0.9578
0.0062 15.0 5790 0.2608 0.9359 0.9372 0.9365 0.9588
0.005 16.0 6176 0.2667 0.9298 0.9407 0.9350 0.9587
0.0045 17.0 6562 0.2741 0.9337 0.9408 0.9371 0.9592
0.0045 18.0 6948 0.2793 0.9342 0.9371 0.9355 0.9589
0.0035 19.0 7334 0.2806 0.9299 0.9391 0.9342 0.9588
0.0034 20.0 7720 0.2804 0.9323 0.9394 0.9356 0.9587

Framework versions

  • Transformers 4.21.2
  • Pytorch 1.7.1
  • Datasets 2.5.1
  • Tokenizers 0.12.1