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ijelid-indobertweet

Token Classification
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PyTorch
TensorBoard
Safetensors
bert
Generated from Trainer
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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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+
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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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+
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+ # ijelid-indobertweet
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+
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+ This model was trained from scratch on the None dataset.
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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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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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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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+
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+
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+ ### Framework versions
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+
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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