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nb-bert-large-user-needs-v2

Safetensors
bert
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  1. README.md +29 -29
  2. model.safetensors +1 -1
README.md CHANGED
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  ---
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- license: apache-2.0
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- base_model: ltg/norbert3-large
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  tags:
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  - generated_from_trainer
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  metrics:
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  # nb-bert-large-user-needs-v2
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- This model is a fine-tuned version of [ltg/norbert3-large](https://huggingface.co/ltg/norbert3-large) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 3.0724
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- - Accuracy: 0.6853
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- - F1: 0.6674
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- - Precision: 0.6636
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- - Recall: 0.6853
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 3e-05
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- - train_batch_size: 4
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  - eval_batch_size: 32
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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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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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- | No log | 1.0 | 375 | 0.8229 | 0.6453 | 0.6076 | 0.6107 | 0.6453 |
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- | 0.9043 | 2.0 | 750 | 0.8588 | 0.6667 | 0.6416 | 0.6207 | 0.6667 |
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- | 0.744 | 3.0 | 1125 | 0.8531 | 0.656 | 0.6300 | 0.6063 | 0.656 |
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- | 0.5288 | 4.0 | 1500 | 1.5591 | 0.6827 | 0.6513 | 0.6425 | 0.6827 |
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- | 0.5288 | 5.0 | 1875 | 2.0799 | 0.6507 | 0.6495 | 0.6493 | 0.6507 |
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- | 0.1999 | 6.0 | 2250 | 2.7613 | 0.664 | 0.6465 | 0.6476 | 0.664 |
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- | 0.0406 | 7.0 | 2625 | 3.0547 | 0.6267 | 0.6044 | 0.6314 | 0.6267 |
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- | 0.0402 | 8.0 | 3000 | 2.7554 | 0.672 | 0.6613 | 0.6515 | 0.672 |
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- | 0.0402 | 9.0 | 3375 | 2.9426 | 0.6587 | 0.6529 | 0.6478 | 0.6587 |
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- | 0.0229 | 10.0 | 3750 | 3.0100 | 0.664 | 0.6505 | 0.6462 | 0.664 |
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- | 0.0075 | 11.0 | 4125 | 2.9582 | 0.656 | 0.6375 | 0.6266 | 0.656 |
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- | 0.0112 | 12.0 | 4500 | 2.9971 | 0.656 | 0.6424 | 0.6335 | 0.656 |
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- | 0.0112 | 13.0 | 4875 | 3.1416 | 0.6587 | 0.6422 | 0.6297 | 0.6587 |
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- | 0.0054 | 14.0 | 5250 | 3.1233 | 0.68 | 0.6597 | 0.6495 | 0.68 |
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- | 0.003 | 15.0 | 5625 | 3.1611 | 0.6773 | 0.6632 | 0.6657 | 0.6773 |
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- | 0.0071 | 16.0 | 6000 | 3.0724 | 0.6853 | 0.6674 | 0.6636 | 0.6853 |
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- | 0.0071 | 17.0 | 6375 | 3.0737 | 0.6667 | 0.6538 | 0.6468 | 0.6667 |
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- | 0.0029 | 18.0 | 6750 | 3.1641 | 0.6747 | 0.6659 | 0.6599 | 0.6747 |
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- | 0.0024 | 19.0 | 7125 | 3.2062 | 0.6693 | 0.6597 | 0.6542 | 0.6693 |
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- | 0.0012 | 20.0 | 7500 | 3.2474 | 0.6747 | 0.6650 | 0.6595 | 0.6747 |
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  ### Framework versions
 
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  ---
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+ license: cc-by-4.0
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+ base_model: NbAiLab/nb-bert-large
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  tags:
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  - generated_from_trainer
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  metrics:
 
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  # nb-bert-large-user-needs-v2
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+ This model is a fine-tuned version of [NbAiLab/nb-bert-large](https://huggingface.co/NbAiLab/nb-bert-large) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.0173
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+ - Accuracy: 0.8
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+ - F1: 0.7945
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+ - Precision: 0.7947
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+ - Recall: 0.8
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 3e-05
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+ - train_batch_size: 8
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  - eval_batch_size: 32
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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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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | No log | 1.0 | 188 | 0.7673 | 0.696 | 0.6619 | 0.6566 | 0.696 |
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+ | No log | 2.0 | 376 | 0.5713 | 0.7707 | 0.7423 | 0.7163 | 0.7707 |
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+ | 0.6847 | 3.0 | 564 | 0.5849 | 0.7653 | 0.7547 | 0.7654 | 0.7653 |
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+ | 0.6847 | 4.0 | 752 | 0.7731 | 0.7467 | 0.7254 | 0.7474 | 0.7467 |
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+ | 0.6847 | 5.0 | 940 | 0.6056 | 0.7733 | 0.7740 | 0.7756 | 0.7733 |
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+ | 0.4443 | 6.0 | 1128 | 0.7752 | 0.792 | 0.7877 | 0.7901 | 0.792 |
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+ | 0.4443 | 7.0 | 1316 | 1.0173 | 0.8 | 0.7945 | 0.7947 | 0.8 |
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+ | 0.2807 | 8.0 | 1504 | 1.1683 | 0.7813 | 0.7789 | 0.7783 | 0.7813 |
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+ | 0.2807 | 9.0 | 1692 | 1.1886 | 0.7893 | 0.7825 | 0.7841 | 0.7893 |
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+ | 0.2807 | 10.0 | 1880 | 1.3052 | 0.776 | 0.7695 | 0.7729 | 0.776 |
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+ | 0.1282 | 11.0 | 2068 | 1.4641 | 0.784 | 0.7769 | 0.7804 | 0.784 |
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+ | 0.1282 | 12.0 | 2256 | 1.5614 | 0.7813 | 0.7716 | 0.7871 | 0.7813 |
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+ | 0.1282 | 13.0 | 2444 | 1.6424 | 0.784 | 0.7774 | 0.7804 | 0.784 |
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+ | 0.0529 | 14.0 | 2632 | 1.7250 | 0.7813 | 0.7767 | 0.7770 | 0.7813 |
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+ | 0.0529 | 15.0 | 2820 | 1.6061 | 0.8 | 0.7934 | 0.8058 | 0.8 |
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+ | 0.0182 | 16.0 | 3008 | 1.7678 | 0.792 | 0.7854 | 0.7908 | 0.792 |
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+ | 0.0182 | 17.0 | 3196 | 1.8226 | 0.7893 | 0.7834 | 0.7849 | 0.7893 |
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+ | 0.0182 | 18.0 | 3384 | 1.8330 | 0.7973 | 0.7906 | 0.7936 | 0.7973 |
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+ | 0.0061 | 19.0 | 3572 | 1.8423 | 0.7947 | 0.7879 | 0.7909 | 0.7947 |
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+ | 0.0061 | 20.0 | 3760 | 1.8536 | 0.7973 | 0.7906 | 0.7936 | 0.7973 |
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  ### Framework versions
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