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NaeemCSECUET18
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xlm-roberta-base-MLTC-rob

Text Classification
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Safetensors
xlm-roberta
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  2. model.safetensors +1 -1
README.md CHANGED
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  This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3590
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- - F1: 0.8582
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- - F1 Weighted: 0.8575
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- - Roc Auc: 0.8540
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- - Accuracy: 0.5861
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- - Hamming Loss: 0.1459
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- - Jaccard Score: 0.7516
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- - Zero One Loss: 0.4139
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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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- | 0.5819 | 1.0 | 73 | 0.5865 | 0.7125 | 0.6535 | 0.6745 | 0.3239 | 0.3252 | 0.5534 | 0.6761 |
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- | 0.5155 | 2.0 | 146 | 0.4923 | 0.7685 | 0.7096 | 0.7602 | 0.3959 | 0.2397 | 0.6240 | 0.6041 |
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- | 0.4172 | 3.0 | 219 | 0.4423 | 0.8240 | 0.8193 | 0.8076 | 0.4884 | 0.1922 | 0.7007 | 0.5116 |
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- | 0.3246 | 4.0 | 292 | 0.3742 | 0.8472 | 0.8469 | 0.8425 | 0.5681 | 0.1575 | 0.7348 | 0.4319 |
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- | 0.3171 | 5.0 | 365 | 0.3589 | 0.8521 | 0.8515 | 0.8489 | 0.5861 | 0.1510 | 0.7423 | 0.4139 |
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- | 0.3444 | 6.0 | 438 | 0.3621 | 0.8534 | 0.8522 | 0.8502 | 0.5758 | 0.1497 | 0.7442 | 0.4242 |
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- | 0.2437 | 7.0 | 511 | 0.3559 | 0.8589 | 0.8583 | 0.8560 | 0.5913 | 0.1440 | 0.7528 | 0.4087 |
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- | 0.249 | 8.0 | 584 | 0.3624 | 0.8545 | 0.8540 | 0.8508 | 0.5810 | 0.1491 | 0.7459 | 0.4190 |
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- | 0.2847 | 9.0 | 657 | 0.3552 | 0.8577 | 0.8574 | 0.8541 | 0.5887 | 0.1459 | 0.7508 | 0.4113 |
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- | 0.2463 | 10.0 | 730 | 0.3590 | 0.8582 | 0.8575 | 0.8540 | 0.5861 | 0.1459 | 0.7516 | 0.4139 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3669
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+ - F1: 0.8586
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+ - F1 Weighted: 0.8585
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+ - Roc Auc: 0.8553
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+ - Accuracy: 0.5964
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+ - Hamming Loss: 0.1446
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+ - Jaccard Score: 0.7522
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+ - Zero One Loss: 0.4036
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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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+ | 0.5856 | 1.0 | 73 | 0.5884 | 0.7201 | 0.6619 | 0.6835 | 0.3393 | 0.3162 | 0.5627 | 0.6607 |
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+ | 0.5053 | 2.0 | 146 | 0.4688 | 0.7718 | 0.7159 | 0.7712 | 0.4139 | 0.2288 | 0.6284 | 0.5861 |
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+ | 0.3929 | 3.0 | 219 | 0.4002 | 0.8410 | 0.8413 | 0.8334 | 0.5347 | 0.1665 | 0.7256 | 0.4653 |
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+ | 0.3293 | 4.0 | 292 | 0.3816 | 0.8471 | 0.8453 | 0.8399 | 0.5527 | 0.1600 | 0.7348 | 0.4473 |
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+ | 0.3242 | 5.0 | 365 | 0.3607 | 0.8550 | 0.8538 | 0.8515 | 0.5784 | 0.1485 | 0.7467 | 0.4216 |
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+ | 0.3228 | 6.0 | 438 | 0.3776 | 0.8495 | 0.8462 | 0.8437 | 0.5707 | 0.1562 | 0.7384 | 0.4293 |
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+ | 0.2713 | 7.0 | 511 | 0.4086 | 0.8453 | 0.8412 | 0.8373 | 0.5630 | 0.1626 | 0.7320 | 0.4370 |
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+ | 0.2519 | 8.0 | 584 | 0.3711 | 0.8534 | 0.8531 | 0.8489 | 0.5861 | 0.1510 | 0.7443 | 0.4139 |
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+ | 0.2724 | 9.0 | 657 | 0.3645 | 0.8629 | 0.8632 | 0.8598 | 0.6067 | 0.1401 | 0.7588 | 0.3933 |
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+ | 0.2484 | 10.0 | 730 | 0.3669 | 0.8586 | 0.8585 | 0.8553 | 0.5964 | 0.1446 | 0.7522 | 0.4036 |
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  ### Framework versions
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