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---
license: apache-2.0
base_model: google-bert/bert-large-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: Intent-classification-BERT-Large-Ashuv3
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Intent-classification-BERT-Large-Ashuv3
This model is a fine-tuned version of [google-bert/bert-large-uncased](https://huggingface.co./google-bert/bert-large-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2610
- Accuracy: 0.8951
- F1: 0.8807
- Precision: 0.8812
- Recall: 0.8820
## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.6762 | 0.24 | 10 | 1.3120 | 0.5280 | 0.4993 | 0.6178 | 0.5370 |
| 0.9717 | 0.49 | 20 | 0.7487 | 0.8571 | 0.8402 | 0.8670 | 0.8455 |
| 0.6375 | 0.73 | 30 | 0.4393 | 0.8509 | 0.8479 | 0.8862 | 0.8548 |
| 0.4006 | 0.98 | 40 | 0.2427 | 0.9068 | 0.9005 | 0.9228 | 0.9075 |
| 0.2291 | 1.22 | 50 | 0.1875 | 0.9068 | 0.8940 | 0.9106 | 0.8902 |
| 0.2634 | 1.46 | 60 | 0.2204 | 0.9068 | 0.8977 | 0.9135 | 0.9051 |
| 0.1916 | 1.71 | 70 | 0.1730 | 0.9130 | 0.9053 | 0.9232 | 0.9123 |
| 0.1881 | 1.95 | 80 | 0.1676 | 0.9130 | 0.9051 | 0.9232 | 0.9133 |
| 0.2692 | 2.2 | 90 | 0.1728 | 0.9068 | 0.8958 | 0.9423 | 0.8790 |
| 0.1425 | 2.44 | 100 | 0.1757 | 0.9068 | 0.8958 | 0.9423 | 0.8790 |
| 0.2674 | 2.68 | 110 | 0.3307 | 0.8758 | 0.8608 | 0.8756 | 0.8713 |
| 0.2385 | 2.93 | 120 | 0.1878 | 0.9006 | 0.8901 | 0.9059 | 0.8988 |
| 0.1868 | 3.17 | 130 | 0.1679 | 0.9130 | 0.9027 | 0.9147 | 0.9097 |
| 0.2281 | 3.41 | 140 | 0.1796 | 0.9130 | 0.9057 | 0.9274 | 0.9133 |
| 0.1459 | 3.66 | 150 | 0.1982 | 0.9068 | 0.8960 | 0.9077 | 0.9049 |
| 0.161 | 3.9 | 160 | 0.2266 | 0.8944 | 0.8772 | 0.9012 | 0.8765 |
| 0.1441 | 4.15 | 170 | 0.2062 | 0.8944 | 0.8889 | 0.9115 | 0.8935 |
| 0.172 | 4.39 | 180 | 0.2208 | 0.9006 | 0.8922 | 0.9216 | 0.8988 |
| 0.1365 | 4.63 | 190 | 0.2088 | 0.9068 | 0.8974 | 0.9244 | 0.9045 |
| 0.1795 | 4.88 | 200 | 0.2011 | 0.8820 | 0.8682 | 0.8936 | 0.8569 |
| 0.204 | 5.12 | 210 | 0.2377 | 0.8820 | 0.8642 | 0.8656 | 0.8721 |
| 0.1409 | 5.37 | 220 | 0.2178 | 0.8944 | 0.8852 | 0.9003 | 0.8776 |
| 0.1771 | 5.61 | 230 | 0.2284 | 0.8758 | 0.8624 | 0.8871 | 0.8511 |
| 0.1926 | 5.85 | 240 | 0.2211 | 0.8944 | 0.8815 | 0.8990 | 0.8761 |
| 0.2142 | 6.1 | 250 | 0.2217 | 0.9193 | 0.9082 | 0.9306 | 0.9130 |
| 0.1125 | 6.34 | 260 | 0.2321 | 0.9006 | 0.8889 | 0.9420 | 0.8702 |
| 0.1473 | 6.59 | 270 | 0.2129 | 0.9130 | 0.9057 | 0.9274 | 0.9133 |
| 0.1468 | 6.83 | 280 | 0.2318 | 0.9130 | 0.9057 | 0.9274 | 0.9133 |
| 0.1951 | 7.07 | 290 | 0.1957 | 0.9006 | 0.8879 | 0.9061 | 0.8788 |
| 0.1659 | 7.32 | 300 | 0.1961 | 0.9006 | 0.8872 | 0.9143 | 0.8752 |
| 0.1265 | 7.56 | 310 | 0.2058 | 0.9130 | 0.9049 | 0.9226 | 0.9097 |
| 0.1774 | 7.8 | 320 | 0.2223 | 0.9068 | 0.8974 | 0.9244 | 0.9045 |
| 0.2609 | 8.05 | 330 | 0.2218 | 0.8944 | 0.8833 | 0.8906 | 0.8811 |
| 0.1079 | 8.29 | 340 | 0.3312 | 0.8820 | 0.8675 | 0.8672 | 0.8680 |
| 0.1729 | 8.54 | 350 | 0.3627 | 0.8696 | 0.8500 | 0.8540 | 0.8554 |
| 0.2337 | 8.78 | 360 | 0.2526 | 0.9006 | 0.8872 | 0.9143 | 0.8752 |
| 0.1573 | 9.02 | 370 | 0.2072 | 0.9130 | 0.9049 | 0.9226 | 0.9097 |
| 0.1843 | 9.27 | 380 | 0.2605 | 0.9068 | 0.8991 | 0.9210 | 0.9085 |
| 0.1521 | 9.51 | 390 | 0.2695 | 0.9006 | 0.8920 | 0.9081 | 0.8966 |
| 0.193 | 9.76 | 400 | 0.3340 | 0.9130 | 0.9039 | 0.9187 | 0.9061 |
| 0.1034 | 10.0 | 410 | 0.3391 | 0.9068 | 0.8948 | 0.9025 | 0.9049 |
| 0.1348 | 10.24 | 420 | 0.3377 | 0.9006 | 0.8902 | 0.8998 | 0.8930 |
| 0.0856 | 10.49 | 430 | 0.3274 | 0.8882 | 0.8768 | 0.8920 | 0.8692 |
| 0.1877 | 10.73 | 440 | 0.3401 | 0.8696 | 0.8498 | 0.8504 | 0.8514 |
| 0.1775 | 10.98 | 450 | 0.4162 | 0.8882 | 0.8708 | 0.8716 | 0.8799 |
| 0.1357 | 11.22 | 460 | 0.3992 | 0.8820 | 0.8652 | 0.8622 | 0.8716 |
| 0.0878 | 11.46 | 470 | 0.3920 | 0.8944 | 0.8803 | 0.8772 | 0.8883 |
| 0.1892 | 11.71 | 480 | 0.3148 | 0.8696 | 0.8499 | 0.8472 | 0.8549 |
| 0.1712 | 11.95 | 490 | 0.3028 | 0.8758 | 0.8589 | 0.8585 | 0.8597 |
| 0.0914 | 12.2 | 500 | 0.3450 | 0.8820 | 0.8688 | 0.8705 | 0.8680 |
| 0.1793 | 12.44 | 510 | 0.3617 | 0.8882 | 0.8758 | 0.8872 | 0.8692 |
| 0.1355 | 12.68 | 520 | 0.4130 | 0.8820 | 0.8688 | 0.8705 | 0.8680 |
| 0.1518 | 12.93 | 530 | 0.5015 | 0.8944 | 0.8798 | 0.8808 | 0.8878 |
| 0.1778 | 13.17 | 540 | 0.3596 | 0.8882 | 0.8716 | 0.8709 | 0.8804 |
| 0.1662 | 13.41 | 550 | 0.3716 | 0.9006 | 0.8864 | 0.8868 | 0.8930 |
| 0.1105 | 13.66 | 560 | 0.3452 | 0.9006 | 0.8874 | 0.8903 | 0.8966 |
| 0.1369 | 13.9 | 570 | 0.3606 | 0.8944 | 0.8807 | 0.8824 | 0.8883 |
| 0.2051 | 14.15 | 580 | 0.3497 | 0.8882 | 0.8750 | 0.8784 | 0.8728 |
| 0.1441 | 14.39 | 590 | 0.4031 | 0.8820 | 0.8664 | 0.8649 | 0.8680 |
| 0.1586 | 14.63 | 600 | 0.3853 | 0.8820 | 0.8664 | 0.8649 | 0.8680 |
| 0.0974 | 14.88 | 610 | 0.4037 | 0.8820 | 0.8664 | 0.8649 | 0.8680 |
| 0.0799 | 15.12 | 620 | 0.5252 | 0.8820 | 0.8688 | 0.8705 | 0.8680 |
| 0.0969 | 15.37 | 630 | 0.5702 | 0.8820 | 0.8691 | 0.8699 | 0.8716 |
| 0.1664 | 15.61 | 640 | 0.5281 | 0.8820 | 0.8688 | 0.8705 | 0.8680 |
| 0.175 | 15.85 | 650 | 0.4865 | 0.8820 | 0.8688 | 0.8705 | 0.8680 |
| 0.1904 | 16.1 | 660 | 0.3893 | 0.8696 | 0.8528 | 0.8520 | 0.8549 |
| 0.1054 | 16.34 | 670 | 0.4320 | 0.8758 | 0.8612 | 0.8636 | 0.8597 |
| 0.1657 | 16.59 | 680 | 0.5669 | 0.8820 | 0.8688 | 0.8705 | 0.8680 |
| 0.1089 | 16.83 | 690 | 0.5642 | 0.8820 | 0.8677 | 0.8649 | 0.8716 |
| 0.0831 | 17.07 | 700 | 0.4782 | 0.8820 | 0.8709 | 0.8744 | 0.8716 |
| 0.1518 | 17.32 | 710 | 0.5122 | 0.8820 | 0.8695 | 0.8720 | 0.8680 |
| 0.1203 | 17.56 | 720 | 0.5720 | 0.8820 | 0.8695 | 0.8720 | 0.8680 |
| 0.1185 | 17.8 | 730 | 0.5798 | 0.8820 | 0.8698 | 0.8703 | 0.8716 |
| 0.1065 | 18.05 | 740 | 0.5495 | 0.8820 | 0.8685 | 0.8701 | 0.8716 |
| 0.13 | 18.29 | 750 | 0.6271 | 0.8820 | 0.8687 | 0.8696 | 0.8716 |
| 0.1382 | 18.54 | 760 | 0.6307 | 0.8758 | 0.8585 | 0.8556 | 0.8633 |
| 0.0979 | 18.78 | 770 | 0.6167 | 0.8758 | 0.8585 | 0.8556 | 0.8633 |
| 0.1328 | 19.02 | 780 | 0.6011 | 0.8758 | 0.8585 | 0.8556 | 0.8633 |
| 0.1561 | 19.27 | 790 | 0.5938 | 0.8696 | 0.8517 | 0.8495 | 0.8549 |
| 0.1638 | 19.51 | 800 | 0.6397 | 0.8696 | 0.8528 | 0.8520 | 0.8549 |
| 0.1358 | 19.76 | 810 | 0.6917 | 0.8758 | 0.8614 | 0.8649 | 0.8597 |
| 0.1298 | 20.0 | 820 | 0.6769 | 0.8696 | 0.8528 | 0.8489 | 0.8585 |
| 0.1102 | 20.24 | 830 | 0.6891 | 0.8758 | 0.8610 | 0.8594 | 0.8669 |
| 0.127 | 20.49 | 840 | 0.6950 | 0.8820 | 0.8685 | 0.8701 | 0.8716 |
| 0.1719 | 20.73 | 850 | 0.6719 | 0.8882 | 0.8754 | 0.8773 | 0.8799 |
| 0.1503 | 20.98 | 860 | 0.6462 | 0.8820 | 0.8675 | 0.8666 | 0.8716 |
| 0.1118 | 21.22 | 870 | 0.6405 | 0.8820 | 0.8690 | 0.8705 | 0.8680 |
| 0.0991 | 21.46 | 880 | 0.6492 | 0.8758 | 0.8614 | 0.8600 | 0.8633 |
| 0.1288 | 21.71 | 890 | 0.7045 | 0.8820 | 0.8688 | 0.8705 | 0.8680 |
| 0.1414 | 21.95 | 900 | 0.7439 | 0.8820 | 0.8688 | 0.8705 | 0.8680 |
| 0.1744 | 22.2 | 910 | 0.7353 | 0.8820 | 0.8688 | 0.8705 | 0.8680 |
| 0.1072 | 22.44 | 920 | 0.7524 | 0.8820 | 0.8688 | 0.8705 | 0.8680 |
| 0.0931 | 22.68 | 930 | 0.7671 | 0.8758 | 0.8614 | 0.8649 | 0.8597 |
| 0.0775 | 22.93 | 940 | 0.7442 | 0.8758 | 0.8614 | 0.8649 | 0.8597 |
| 0.0713 | 23.17 | 950 | 0.7456 | 0.8758 | 0.8614 | 0.8649 | 0.8597 |
| 0.1027 | 23.41 | 960 | 0.7528 | 0.8820 | 0.8664 | 0.8649 | 0.8680 |
| 0.1163 | 23.66 | 970 | 0.7503 | 0.8820 | 0.8664 | 0.8649 | 0.8680 |
| 0.1067 | 23.9 | 980 | 0.7359 | 0.8758 | 0.8622 | 0.8660 | 0.8597 |
| 0.0955 | 24.15 | 990 | 0.7457 | 0.8820 | 0.8676 | 0.8687 | 0.8680 |
| 0.0874 | 24.39 | 1000 | 0.7663 | 0.8820 | 0.8685 | 0.8701 | 0.8716 |
| 0.0865 | 24.63 | 1010 | 0.7761 | 0.8820 | 0.8685 | 0.8701 | 0.8716 |
| 0.1378 | 24.88 | 1020 | 0.7761 | 0.8820 | 0.8691 | 0.8699 | 0.8716 |
| 0.1411 | 25.12 | 1030 | 0.7714 | 0.8820 | 0.8676 | 0.8687 | 0.8680 |
| 0.1034 | 25.37 | 1040 | 0.7662 | 0.8820 | 0.8685 | 0.8700 | 0.8680 |
| 0.0709 | 25.61 | 1050 | 0.7720 | 0.8820 | 0.8670 | 0.8681 | 0.8680 |
| 0.1286 | 25.85 | 1060 | 0.7809 | 0.8820 | 0.8670 | 0.8681 | 0.8680 |
| 0.1191 | 26.1 | 1070 | 0.7861 | 0.8820 | 0.8676 | 0.8687 | 0.8680 |
| 0.0902 | 26.34 | 1080 | 0.7888 | 0.8820 | 0.8691 | 0.8699 | 0.8716 |
| 0.1054 | 26.59 | 1090 | 0.7894 | 0.8820 | 0.8698 | 0.8703 | 0.8716 |
| 0.1142 | 26.83 | 1100 | 0.7914 | 0.8820 | 0.8691 | 0.8699 | 0.8716 |
| 0.1175 | 27.07 | 1110 | 0.7923 | 0.8820 | 0.8691 | 0.8699 | 0.8716 |
| 0.1319 | 27.32 | 1120 | 0.7938 | 0.8820 | 0.8685 | 0.8701 | 0.8716 |
| 0.1181 | 27.56 | 1130 | 0.7967 | 0.8820 | 0.8685 | 0.8701 | 0.8716 |
| 0.0858 | 27.8 | 1140 | 0.8003 | 0.8820 | 0.8685 | 0.8701 | 0.8716 |
| 0.0697 | 28.05 | 1150 | 0.8025 | 0.8820 | 0.8685 | 0.8701 | 0.8716 |
| 0.0644 | 28.29 | 1160 | 0.8050 | 0.8820 | 0.8685 | 0.8701 | 0.8716 |
| 0.1123 | 28.54 | 1170 | 0.8063 | 0.8820 | 0.8685 | 0.8701 | 0.8716 |
| 0.0998 | 28.78 | 1180 | 0.8078 | 0.8820 | 0.8685 | 0.8701 | 0.8716 |
| 0.1297 | 29.02 | 1190 | 0.8095 | 0.8820 | 0.8685 | 0.8701 | 0.8716 |
| 0.1133 | 29.27 | 1200 | 0.8094 | 0.8820 | 0.8685 | 0.8701 | 0.8716 |
| 0.1122 | 29.51 | 1210 | 0.8095 | 0.8820 | 0.8685 | 0.8701 | 0.8716 |
| 0.1115 | 29.76 | 1220 | 0.8096 | 0.8820 | 0.8685 | 0.8701 | 0.8716 |
| 0.0692 | 30.0 | 1230 | 0.8095 | 0.8820 | 0.8685 | 0.8701 | 0.8716 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2
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