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PhoBertLexical-finetuned_70KURL_daydu

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roberta
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  1. README.md +146 -0
  2. config.json +37 -0
  3. model.safetensors +3 -0
  4. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ base_model: vinai/phobert-base-v2
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ - f1
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+ model-index:
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+ - name: PhoBertLexical-finetuned_70KURL_daydu
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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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+ # PhoBertLexical-finetuned_70KURL_daydu
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+
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+ This model is a fine-tuned version of [vinai/phobert-base-v2](https://huggingface.co/vinai/phobert-base-v2) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2260
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+ - Accuracy: 0.9670
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+ - F1: 0.9671
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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: 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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+ - 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 | Accuracy | F1 |
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+ |:-------------:|:-------:|:-----:|:---------------:|:--------:|:------:|
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+ | No log | 0.2326 | 200 | 0.1641 | 0.9425 | 0.9417 |
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+ | No log | 0.4651 | 400 | 0.1297 | 0.9576 | 0.9580 |
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+ | No log | 0.6977 | 600 | 0.1202 | 0.9590 | 0.9595 |
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+ | No log | 0.9302 | 800 | 0.1118 | 0.9645 | 0.9647 |
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+ | 0.1684 | 1.1628 | 1000 | 0.1167 | 0.9611 | 0.9615 |
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+ | 0.1684 | 1.3953 | 1200 | 0.1192 | 0.9615 | 0.9619 |
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+ | 0.1684 | 1.6279 | 1400 | 0.1101 | 0.9662 | 0.9665 |
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+ | 0.1684 | 1.8605 | 1600 | 0.1054 | 0.9677 | 0.9678 |
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+ | 0.1023 | 2.0930 | 1800 | 0.1181 | 0.9650 | 0.9651 |
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+ | 0.1023 | 2.3256 | 2000 | 0.1011 | 0.9703 | 0.9704 |
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+ | 0.1023 | 2.5581 | 2200 | 0.1091 | 0.9687 | 0.9687 |
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+ | 0.1023 | 2.7907 | 2400 | 0.1048 | 0.9678 | 0.9678 |
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+ | 0.0844 | 3.0233 | 2600 | 0.1147 | 0.9681 | 0.9681 |
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+ | 0.0844 | 3.2558 | 2800 | 0.1254 | 0.9659 | 0.9661 |
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+ | 0.0844 | 3.4884 | 3000 | 0.1007 | 0.9701 | 0.9702 |
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+ | 0.0844 | 3.7209 | 3200 | 0.1102 | 0.9654 | 0.9657 |
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+ | 0.0844 | 3.9535 | 3400 | 0.1134 | 0.9687 | 0.9689 |
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+ | 0.0696 | 4.1860 | 3600 | 0.1093 | 0.9666 | 0.9668 |
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+ | 0.0696 | 4.4186 | 3800 | 0.1081 | 0.9672 | 0.9674 |
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+ | 0.0696 | 4.6512 | 4000 | 0.1141 | 0.9690 | 0.9691 |
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+ | 0.0696 | 4.8837 | 4200 | 0.1263 | 0.9647 | 0.9650 |
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+ | 0.0591 | 5.1163 | 4400 | 0.1361 | 0.9651 | 0.9653 |
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+ | 0.0591 | 5.3488 | 4600 | 0.1291 | 0.9669 | 0.9669 |
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+ | 0.0591 | 5.5814 | 4800 | 0.1378 | 0.9635 | 0.9634 |
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+ | 0.0591 | 5.8140 | 5000 | 0.1402 | 0.9628 | 0.9632 |
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+ | 0.0468 | 6.0465 | 5200 | 0.1280 | 0.9707 | 0.9707 |
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+ | 0.0468 | 6.2791 | 5400 | 0.1357 | 0.9690 | 0.9690 |
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+ | 0.0468 | 6.5116 | 5600 | 0.1311 | 0.9696 | 0.9697 |
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+ | 0.0468 | 6.7442 | 5800 | 0.1419 | 0.9677 | 0.9678 |
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+ | 0.0468 | 6.9767 | 6000 | 0.1252 | 0.9702 | 0.9704 |
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+ | 0.0413 | 7.2093 | 6200 | 0.1386 | 0.9656 | 0.9658 |
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+ | 0.0413 | 7.4419 | 6400 | 0.1673 | 0.9642 | 0.9645 |
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+ | 0.0413 | 7.6744 | 6600 | 0.1526 | 0.9646 | 0.9646 |
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+ | 0.0413 | 7.9070 | 6800 | 0.1427 | 0.9701 | 0.9702 |
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+ | 0.0341 | 8.1395 | 7000 | 0.1487 | 0.9687 | 0.9688 |
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+ | 0.0341 | 8.3721 | 7200 | 0.1524 | 0.9663 | 0.9664 |
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+ | 0.0341 | 8.6047 | 7400 | 0.1489 | 0.9680 | 0.9683 |
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+ | 0.0341 | 8.8372 | 7600 | 0.1419 | 0.9698 | 0.9699 |
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+ | 0.0286 | 9.0698 | 7800 | 0.1817 | 0.9652 | 0.9654 |
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+ | 0.0286 | 9.3023 | 8000 | 0.1744 | 0.9696 | 0.9696 |
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+ | 0.0286 | 9.5349 | 8200 | 0.1645 | 0.9692 | 0.9693 |
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+ | 0.0286 | 9.7674 | 8400 | 0.1624 | 0.9695 | 0.9697 |
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+ | 0.0235 | 10.0 | 8600 | 0.1638 | 0.9659 | 0.9660 |
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+ | 0.0235 | 10.2326 | 8800 | 0.1889 | 0.9652 | 0.9652 |
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+ | 0.0235 | 10.4651 | 9000 | 0.1929 | 0.9645 | 0.9645 |
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+ | 0.0235 | 10.6977 | 9200 | 0.1802 | 0.9674 | 0.9676 |
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+ | 0.0235 | 10.9302 | 9400 | 0.1879 | 0.9647 | 0.9649 |
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+ | 0.0199 | 11.1628 | 9600 | 0.1800 | 0.9682 | 0.9682 |
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+ | 0.0199 | 11.3953 | 9800 | 0.2004 | 0.9652 | 0.9652 |
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+ | 0.0199 | 11.6279 | 10000 | 0.1883 | 0.9671 | 0.9672 |
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+ | 0.0199 | 11.8605 | 10200 | 0.1840 | 0.9692 | 0.9694 |
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+ | 0.0178 | 12.0930 | 10400 | 0.1986 | 0.9660 | 0.9660 |
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+ | 0.0178 | 12.3256 | 10600 | 0.1970 | 0.9656 | 0.9658 |
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+ | 0.0178 | 12.5581 | 10800 | 0.1952 | 0.9682 | 0.9683 |
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+ | 0.0178 | 12.7907 | 11000 | 0.1931 | 0.9661 | 0.9660 |
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+ | 0.0152 | 13.0233 | 11200 | 0.1962 | 0.9655 | 0.9656 |
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+ | 0.0152 | 13.2558 | 11400 | 0.2098 | 0.9662 | 0.9662 |
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+ | 0.0152 | 13.4884 | 11600 | 0.2088 | 0.9655 | 0.9654 |
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+ | 0.0152 | 13.7209 | 11800 | 0.2031 | 0.9658 | 0.9658 |
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+ | 0.0152 | 13.9535 | 12000 | 0.2044 | 0.9666 | 0.9666 |
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+ | 0.0118 | 14.1860 | 12200 | 0.2025 | 0.9674 | 0.9676 |
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+ | 0.0118 | 14.4186 | 12400 | 0.2159 | 0.9656 | 0.9656 |
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+ | 0.0118 | 14.6512 | 12600 | 0.2098 | 0.9665 | 0.9666 |
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+ | 0.0118 | 14.8837 | 12800 | 0.1995 | 0.9676 | 0.9677 |
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+ | 0.0105 | 15.1163 | 13000 | 0.2108 | 0.9673 | 0.9674 |
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+ | 0.0105 | 15.3488 | 13200 | 0.2233 | 0.9652 | 0.9652 |
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+ | 0.0105 | 15.5814 | 13400 | 0.2219 | 0.9654 | 0.9654 |
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+ | 0.0105 | 15.8140 | 13600 | 0.2251 | 0.9665 | 0.9665 |
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+ | 0.0094 | 16.0465 | 13800 | 0.2199 | 0.9660 | 0.9661 |
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+ | 0.0094 | 16.2791 | 14000 | 0.2344 | 0.9652 | 0.9652 |
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+ | 0.0094 | 16.5116 | 14200 | 0.2260 | 0.9669 | 0.9670 |
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+ | 0.0094 | 16.7442 | 14400 | 0.2123 | 0.9674 | 0.9675 |
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+ | 0.0094 | 16.9767 | 14600 | 0.2129 | 0.9678 | 0.9679 |
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+ | 0.0072 | 17.2093 | 14800 | 0.2134 | 0.9676 | 0.9677 |
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+ | 0.0072 | 17.4419 | 15000 | 0.2235 | 0.9663 | 0.9663 |
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+ | 0.0072 | 17.6744 | 15200 | 0.2199 | 0.9672 | 0.9672 |
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+ | 0.0072 | 17.9070 | 15400 | 0.2280 | 0.9654 | 0.9655 |
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+ | 0.0069 | 18.1395 | 15600 | 0.2242 | 0.9670 | 0.9670 |
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+ | 0.0069 | 18.3721 | 15800 | 0.2188 | 0.9679 | 0.9680 |
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+ | 0.0069 | 18.6047 | 16000 | 0.2202 | 0.9676 | 0.9676 |
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+ | 0.0069 | 18.8372 | 16200 | 0.2261 | 0.9664 | 0.9664 |
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+ | 0.0062 | 19.0698 | 16400 | 0.2264 | 0.9667 | 0.9668 |
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+ | 0.0062 | 19.3023 | 16600 | 0.2238 | 0.9666 | 0.9667 |
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+ | 0.0062 | 19.5349 | 16800 | 0.2243 | 0.9669 | 0.9670 |
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+ | 0.0062 | 19.7674 | 17000 | 0.2262 | 0.9671 | 0.9671 |
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+ | 0.0055 | 20.0 | 17200 | 0.2260 | 0.9670 | 0.9671 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.2
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+ - Pytorch 2.1.2
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+ - Datasets 2.19.2
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+ - Tokenizers 0.19.1
config.json ADDED
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+ {
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+ "_name_or_path": "vinai/phobert-base-v2",
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+ "architectures": [
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+ "PhoBertLexical"
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+ ],
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+ "attention_probs_dropout_prob": 0.1,
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+ "bos_token_id": 0,
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+ "classifier_dropout": null,
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+ "eos_token_id": 2,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 768,
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+ "id2label": {
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+ "0": "B\u00ecnh th\u01b0\u1eddng",
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+ "1": "T\u00ednh nhi\u1ec7m th\u1ea5p"
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+ "intermediate_size": 3072,
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+ },
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+ "layer_norm_eps": 1e-05,
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+ "max_position_embeddings": 258,
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+ "model_type": "roberta",
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+ "num_attention_heads": 12,
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+ "num_classes": 2,
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+ "num_hidden_layers": 12,
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+ "pad_token_id": 1,
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+ "position_embedding_type": "absolute",
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+ "tokenizer_class": "PhobertTokenizer",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.41.2",
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+ "type_vocab_size": 1,
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+ "use_cache": true,
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+ "vocab_size": 64001
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+ }
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