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BERT_Text_classification_clean

Text Classification
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Safetensors
bert
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  1. README.md +48 -18
  2. model.safetensors +1 -1
README.md CHANGED
@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5208
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- - Accuracy: 0.9028
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- - F1: 0.8924
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- - Precision: 0.8990
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- - Recall: 0.8925
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  ## Model description
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@@ -49,25 +49,55 @@ The following hyperparameters were used during training:
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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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- - lr_scheduler_warmup_steps: 100
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  - num_epochs: 3
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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- | 1.6803 | 0.24 | 50 | 1.2419 | 0.7613 | 0.7374 | 0.7493 | 0.7460 |
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- | 0.6367 | 0.48 | 100 | 0.4523 | 0.8437 | 0.8358 | 0.8377 | 0.8357 |
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- | 0.2756 | 0.71 | 150 | 0.4543 | 0.8625 | 0.8550 | 0.8576 | 0.8544 |
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- | 0.2569 | 0.95 | 200 | 0.4377 | 0.8845 | 0.8715 | 0.8791 | 0.8727 |
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- | 0.1044 | 1.19 | 250 | 0.5032 | 0.8903 | 0.8793 | 0.8828 | 0.8795 |
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- | 0.0745 | 1.43 | 300 | 0.5342 | 0.8912 | 0.8791 | 0.8881 | 0.8798 |
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- | 0.0906 | 1.67 | 350 | 0.5484 | 0.8992 | 0.8880 | 0.8956 | 0.8886 |
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- | 0.0839 | 1.9 | 400 | 0.5337 | 0.8939 | 0.8827 | 0.8858 | 0.8830 |
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- | 0.0474 | 2.14 | 450 | 0.5237 | 0.8983 | 0.8876 | 0.8938 | 0.8879 |
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- | 0.0346 | 2.38 | 500 | 0.4822 | 0.9037 | 0.8939 | 0.9005 | 0.8939 |
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- | 0.0243 | 2.62 | 550 | 0.5014 | 0.9019 | 0.8916 | 0.8964 | 0.8917 |
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- | 0.0181 | 2.86 | 600 | 0.5208 | 0.9028 | 0.8924 | 0.8990 | 0.8925 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5562
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+ - Accuracy: 0.8708
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+ - F1: 0.8634
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+ - Precision: 0.8673
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+ - Recall: 0.8632
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  ## Model description
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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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+ - lr_scheduler_warmup_steps: 150
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  - num_epochs: 3
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | 2.9977 | 0.07 | 50 | 2.9491 | 0.0609 | 0.0334 | 0.0689 | 0.0589 |
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+ | 2.6422 | 0.14 | 100 | 2.1816 | 0.4223 | 0.3423 | 0.4771 | 0.4054 |
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+ | 1.8378 | 0.21 | 150 | 1.4580 | 0.6045 | 0.5381 | 0.5940 | 0.5858 |
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+ | 1.2155 | 0.28 | 200 | 1.0783 | 0.7019 | 0.6600 | 0.6722 | 0.6851 |
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+ | 0.8869 | 0.35 | 250 | 0.8923 | 0.7491 | 0.7237 | 0.7474 | 0.7309 |
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+ | 0.821 | 0.42 | 300 | 0.8259 | 0.7667 | 0.7453 | 0.7527 | 0.7494 |
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+ | 0.7908 | 0.49 | 350 | 0.8119 | 0.7694 | 0.7417 | 0.7745 | 0.7510 |
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+ | 0.6891 | 0.56 | 400 | 0.7503 | 0.7827 | 0.7566 | 0.7834 | 0.7659 |
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+ | 0.6517 | 0.64 | 450 | 0.7300 | 0.7840 | 0.7592 | 0.8025 | 0.7668 |
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+ | 0.582 | 0.71 | 500 | 0.7140 | 0.8003 | 0.7874 | 0.7946 | 0.7868 |
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+ | 0.5354 | 0.78 | 550 | 0.7101 | 0.7789 | 0.7730 | 0.7973 | 0.7731 |
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+ | 0.6222 | 0.85 | 600 | 0.6393 | 0.8105 | 0.7917 | 0.8066 | 0.7941 |
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+ | 0.5159 | 0.92 | 650 | 0.6774 | 0.7946 | 0.7771 | 0.8021 | 0.7792 |
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+ | 0.5611 | 0.99 | 700 | 0.6016 | 0.8218 | 0.8030 | 0.8211 | 0.8064 |
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+ | 0.3468 | 1.06 | 750 | 0.6555 | 0.8113 | 0.7963 | 0.8126 | 0.7972 |
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+ | 0.3636 | 1.13 | 800 | 0.6447 | 0.8139 | 0.8015 | 0.8182 | 0.8014 |
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+ | 0.2689 | 1.2 | 850 | 0.5984 | 0.8332 | 0.8230 | 0.8294 | 0.8233 |
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+ | 0.3393 | 1.27 | 900 | 0.6076 | 0.8334 | 0.8253 | 0.8337 | 0.8254 |
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+ | 0.3395 | 1.34 | 950 | 0.5933 | 0.8364 | 0.8253 | 0.8320 | 0.8250 |
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+ | 0.2421 | 1.41 | 1000 | 0.5973 | 0.8371 | 0.8256 | 0.8369 | 0.8254 |
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+ | 0.2708 | 1.48 | 1050 | 0.6241 | 0.8348 | 0.8244 | 0.8311 | 0.8252 |
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+ | 0.2972 | 1.55 | 1100 | 0.6012 | 0.8395 | 0.8292 | 0.8400 | 0.8274 |
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+ | 0.2694 | 1.62 | 1150 | 0.6092 | 0.8425 | 0.8348 | 0.8497 | 0.8352 |
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+ | 0.2738 | 1.69 | 1200 | 0.5839 | 0.8501 | 0.8426 | 0.8474 | 0.8414 |
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+ | 0.2731 | 1.77 | 1250 | 0.5573 | 0.8542 | 0.8446 | 0.8491 | 0.8444 |
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+ | 0.2472 | 1.84 | 1300 | 0.5565 | 0.8546 | 0.8476 | 0.8547 | 0.8469 |
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+ | 0.1901 | 1.91 | 1350 | 0.5555 | 0.8586 | 0.8521 | 0.8568 | 0.8519 |
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+ | 0.217 | 1.98 | 1400 | 0.5737 | 0.8548 | 0.8446 | 0.8549 | 0.8447 |
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+ | 0.1559 | 2.05 | 1450 | 0.5715 | 0.8578 | 0.8494 | 0.8559 | 0.8481 |
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+ | 0.1457 | 2.12 | 1500 | 0.5425 | 0.8650 | 0.8570 | 0.8605 | 0.8566 |
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+ | 0.1067 | 2.19 | 1550 | 0.5734 | 0.8655 | 0.8564 | 0.8644 | 0.8560 |
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+ | 0.1183 | 2.26 | 1600 | 0.5509 | 0.8659 | 0.8587 | 0.8617 | 0.8585 |
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+ | 0.1507 | 2.33 | 1650 | 0.5806 | 0.8609 | 0.8528 | 0.8561 | 0.8529 |
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+ | 0.1446 | 2.4 | 1700 | 0.5629 | 0.8700 | 0.8633 | 0.8683 | 0.8626 |
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+ | 0.1234 | 2.47 | 1750 | 0.5690 | 0.8667 | 0.8595 | 0.8625 | 0.8595 |
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+ | 0.0921 | 2.54 | 1800 | 0.5597 | 0.8640 | 0.8567 | 0.8599 | 0.8566 |
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+ | 0.0866 | 2.61 | 1850 | 0.5759 | 0.8664 | 0.8593 | 0.8631 | 0.8586 |
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+ | 0.0874 | 2.68 | 1900 | 0.5790 | 0.8680 | 0.8599 | 0.8658 | 0.8599 |
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+ | 0.133 | 2.75 | 1950 | 0.5633 | 0.8696 | 0.8625 | 0.8674 | 0.8624 |
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+ | 0.1309 | 2.82 | 2000 | 0.5580 | 0.8712 | 0.8640 | 0.8678 | 0.8640 |
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+ | 0.1011 | 2.9 | 2050 | 0.5584 | 0.8711 | 0.8637 | 0.8680 | 0.8636 |
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+ | 0.0857 | 2.97 | 2100 | 0.5562 | 0.8708 | 0.8634 | 0.8673 | 0.8632 |
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  ### Framework versions
model.safetensors CHANGED
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