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NaeemCSECUET18
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bangla-bert-base-MLTC-BB2

Text Classification
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bert
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  1. README.md +17 -15
  2. model.safetensors +1 -1
README.md CHANGED
@@ -18,14 +18,14 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [sagorsarker/bangla-bert-base](https://huggingface.co/sagorsarker/bangla-bert-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4005
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  - F1: 0.8514
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- - F1 Weighted: 0.8504
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- - Roc Auc: 0.8470
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- - Accuracy: 0.5424
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- - Hamming Loss: 0.1530
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- - Jaccard Score: 0.7413
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- - Zero One Loss: 0.4576
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | F1 | F1 Weighted | Roc Auc | Accuracy | Hamming Loss | Jaccard Score | Zero One Loss |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:-----------:|:-------:|:--------:|:------------:|:-------------:|:-------------:|
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- | 0.4015 | 1.0 | 73 | 0.4027 | 0.8246 | 0.8201 | 0.8206 | 0.5039 | 0.1793 | 0.7016 | 0.4961 |
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- | 0.3579 | 2.0 | 146 | 0.3583 | 0.8541 | 0.8548 | 0.8522 | 0.5553 | 0.1478 | 0.7453 | 0.4447 |
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- | 0.2831 | 3.0 | 219 | 0.3768 | 0.8429 | 0.8402 | 0.8360 | 0.5398 | 0.1639 | 0.7284 | 0.4602 |
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- | 0.1799 | 4.0 | 292 | 0.3565 | 0.8534 | 0.8534 | 0.8489 | 0.5604 | 0.1510 | 0.7443 | 0.4396 |
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- | 0.1671 | 5.0 | 365 | 0.3724 | 0.8552 | 0.8547 | 0.8508 | 0.5681 | 0.1491 | 0.7470 | 0.4319 |
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- | 0.1451 | 6.0 | 438 | 0.3773 | 0.8493 | 0.8484 | 0.8477 | 0.5450 | 0.1523 | 0.7381 | 0.4550 |
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- | 0.0899 | 7.0 | 511 | 0.3986 | 0.8502 | 0.8494 | 0.8457 | 0.5398 | 0.1542 | 0.7394 | 0.4602 |
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- | 0.0744 | 8.0 | 584 | 0.4005 | 0.8514 | 0.8504 | 0.8470 | 0.5424 | 0.1530 | 0.7413 | 0.4576 |
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [sagorsarker/bangla-bert-base](https://huggingface.co/sagorsarker/bangla-bert-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3996
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  - F1: 0.8514
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+ - F1 Weighted: 0.8510
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+ - Roc Auc: 0.8483
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+ - Accuracy: 0.5373
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+ - Hamming Loss: 0.1517
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+ - Jaccard Score: 0.7412
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+ - Zero One Loss: 0.4627
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | F1 | F1 Weighted | Roc Auc | Accuracy | Hamming Loss | Jaccard Score | Zero One Loss |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:-----------:|:-------:|:--------:|:------------:|:-------------:|:-------------:|
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+ | 0.3931 | 1.0 | 73 | 0.3859 | 0.8319 | 0.8312 | 0.8310 | 0.5244 | 0.1690 | 0.7123 | 0.4756 |
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+ | 0.3635 | 2.0 | 146 | 0.3638 | 0.8540 | 0.8546 | 0.8528 | 0.5707 | 0.1472 | 0.7453 | 0.4293 |
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+ | 0.2688 | 3.0 | 219 | 0.3676 | 0.8483 | 0.8465 | 0.8425 | 0.5553 | 0.1575 | 0.7366 | 0.4447 |
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+ | 0.1841 | 4.0 | 292 | 0.3600 | 0.8562 | 0.8558 | 0.8534 | 0.5758 | 0.1465 | 0.7486 | 0.4242 |
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+ | 0.1701 | 5.0 | 365 | 0.3677 | 0.8568 | 0.8565 | 0.8528 | 0.5681 | 0.1472 | 0.7495 | 0.4319 |
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+ | 0.1499 | 6.0 | 438 | 0.3701 | 0.8551 | 0.8541 | 0.8534 | 0.5630 | 0.1465 | 0.7469 | 0.4370 |
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+ | 0.1034 | 7.0 | 511 | 0.3825 | 0.8582 | 0.8576 | 0.8540 | 0.5527 | 0.1459 | 0.7516 | 0.4473 |
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+ | 0.0793 | 8.0 | 584 | 0.4103 | 0.8443 | 0.8428 | 0.8393 | 0.5167 | 0.1607 | 0.7306 | 0.4833 |
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+ | 0.0801 | 9.0 | 657 | 0.3960 | 0.8484 | 0.8484 | 0.8470 | 0.5373 | 0.1530 | 0.7367 | 0.4627 |
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+ | 0.0812 | 10.0 | 730 | 0.3996 | 0.8514 | 0.8510 | 0.8483 | 0.5373 | 0.1517 | 0.7412 | 0.4627 |
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  ### Framework versions
model.safetensors CHANGED
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