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favs-filtersort-multilabel-classification-bert-base-cased

Text Classification
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PyTorch
bert
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Eval Results
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update model card README.md

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@@ -22,10 +22,10 @@ model-index:
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  metrics:
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  - name: F1
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  type: f1
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- value: 0.823529411764706
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  - name: Accuracy
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  type: accuracy
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- value: 0.0
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -35,10 +35,10 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the filter_sort dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4283
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- - F1: 0.8235
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- - Roc Auc: 0.9058
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- - Accuracy: 0.0
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  ## Model description
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@@ -69,26 +69,26 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
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- | No log | 1.0 | 9 | 0.5901 | 0.6087 | 0.7289 | 0.0 |
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- | 0.665 | 2.0 | 18 | 0.5667 | 0.4545 | 0.6201 | 0.0 |
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- | 0.6099 | 3.0 | 27 | 0.5573 | 0.5 | 0.6558 | 0.0 |
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- | 0.5463 | 4.0 | 36 | 0.5561 | 0.3889 | 0.5966 | 0.0 |
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- | 0.5071 | 5.0 | 45 | 0.5484 | 0.3889 | 0.5966 | 0.0 |
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- | 0.4669 | 6.0 | 54 | 0.5462 | 0.4324 | 0.6193 | 0.0 |
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- | 0.4371 | 7.0 | 63 | 0.5326 | 0.4737 | 0.6420 | 0.0 |
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- | 0.4145 | 8.0 | 72 | 0.5202 | 0.5854 | 0.7102 | 0.0 |
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- | 0.3959 | 9.0 | 81 | 0.5020 | 0.6364 | 0.7468 | 0.0 |
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- | 0.3733 | 10.0 | 90 | 0.4944 | 0.6364 | 0.7468 | 0.0 |
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- | 0.3733 | 11.0 | 99 | 0.4675 | 0.7234 | 0.8149 | 0.0 |
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- | 0.3622 | 12.0 | 108 | 0.4626 | 0.7843 | 0.8742 | 0.0 |
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- | 0.3382 | 13.0 | 117 | 0.4499 | 0.8077 | 0.8969 | 0.0 |
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- | 0.3341 | 14.0 | 126 | 0.4482 | 0.8077 | 0.8969 | 0.0 |
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- | 0.315 | 15.0 | 135 | 0.4332 | 0.8077 | 0.8969 | 0.0 |
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- | 0.3253 | 16.0 | 144 | 0.4283 | 0.8235 | 0.9058 | 0.0 |
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- | 0.3031 | 17.0 | 153 | 0.4246 | 0.8077 | 0.8969 | 0.0 |
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- | 0.3071 | 18.0 | 162 | 0.4155 | 0.8077 | 0.8969 | 0.0 |
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- | 0.2944 | 19.0 | 171 | 0.4129 | 0.8077 | 0.8969 | 0.0 |
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- | 0.2996 | 20.0 | 180 | 0.4129 | 0.8077 | 0.8969 | 0.0 |
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  ### Framework versions
 
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  metrics:
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  - name: F1
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  type: f1
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+ value: 0.7887323943661971
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  - name: Accuracy
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  type: accuracy
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+ value: 0.3
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the filter_sort dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2822
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+ - F1: 0.7887
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+ - Roc Auc: 0.8437
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+ - Accuracy: 0.3
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
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+ | 0.6319 | 1.0 | 12 | 0.5814 | 0.4889 | 0.6714 | 0.0 |
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+ | 0.5697 | 2.0 | 24 | 0.5046 | 0.6111 | 0.7401 | 0.0 |
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+ | 0.5224 | 3.0 | 36 | 0.4393 | 0.6923 | 0.8004 | 0.0 |
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+ | 0.4666 | 4.0 | 48 | 0.4048 | 0.6835 | 0.7965 | 0.0 |
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+ | 0.4188 | 5.0 | 60 | 0.3795 | 0.6933 | 0.7952 | 0.0 |
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+ | 0.4023 | 6.0 | 72 | 0.3634 | 0.7027 | 0.7990 | 0.0 |
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+ | 0.3776 | 7.0 | 84 | 0.3526 | 0.7143 | 0.7976 | 0.0 |
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+ | 0.3635 | 8.0 | 96 | 0.3423 | 0.7143 | 0.7976 | 0.0 |
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+ | 0.3648 | 9.0 | 108 | 0.3288 | 0.7059 | 0.7886 | 0.0 |
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+ | 0.3284 | 10.0 | 120 | 0.3192 | 0.7429 | 0.8142 | 0.2 |
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+ | 0.3267 | 11.0 | 132 | 0.3151 | 0.7353 | 0.8052 | 0.1 |
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+ | 0.3113 | 12.0 | 144 | 0.3066 | 0.7536 | 0.8181 | 0.2 |
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+ | 0.3043 | 13.0 | 156 | 0.3018 | 0.7606 | 0.8271 | 0.3 |
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+ | 0.2924 | 14.0 | 168 | 0.2940 | 0.7606 | 0.8271 | 0.3 |
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+ | 0.2843 | 15.0 | 180 | 0.2936 | 0.7714 | 0.8309 | 0.3 |
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+ | 0.2794 | 16.0 | 192 | 0.2856 | 0.7778 | 0.8399 | 0.3 |
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+ | 0.2678 | 17.0 | 204 | 0.2860 | 0.7714 | 0.8309 | 0.3 |
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+ | 0.2631 | 18.0 | 216 | 0.2822 | 0.7887 | 0.8437 | 0.3 |
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+ | 0.269 | 19.0 | 228 | 0.2806 | 0.7887 | 0.8437 | 0.3 |
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+ | 0.2609 | 20.0 | 240 | 0.2799 | 0.7887 | 0.8437 | 0.3 |
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  ### Framework versions