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

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

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@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: F1
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  type: f1
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- value: 0.7887323943661971
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  - name: Accuracy
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  type: accuracy
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  value: 0.3
@@ -35,9 +35,9 @@ 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: 0.2822
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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
@@ -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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- | 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
 
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  metrics:
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  - name: F1
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  type: f1
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+ value: 0.767123287671233
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  - name: Accuracy
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  type: accuracy
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  value: 0.3
 
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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: 0.2847
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+ - F1: 0.7671
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+ - Roc Auc: 0.8361
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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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+ | 0.7037 | 1.0 | 12 | 0.6056 | 0.5714 | 0.7341 | 0.0 |
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+ | 0.5962 | 2.0 | 24 | 0.5212 | 0.5067 | 0.6787 | 0.0 |
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+ | 0.5393 | 3.0 | 36 | 0.4396 | 0.6197 | 0.7439 | 0.1 |
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+ | 0.4682 | 4.0 | 48 | 0.3963 | 0.5714 | 0.7079 | 0.0 |
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+ | 0.409 | 5.0 | 60 | 0.3710 | 0.6061 | 0.7297 | 0.0 |
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+ | 0.3923 | 6.0 | 72 | 0.3571 | 0.6286 | 0.7477 | 0.1 |
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+ | 0.3682 | 7.0 | 84 | 0.3439 | 0.6849 | 0.7862 | 0.2 |
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+ | 0.367 | 8.0 | 96 | 0.3286 | 0.6479 | 0.7605 | 0.1 |
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+ | 0.3633 | 9.0 | 108 | 0.3194 | 0.6761 | 0.7772 | 0.2 |
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+ | 0.3359 | 10.0 | 120 | 0.3145 | 0.6761 | 0.7772 | 0.2 |
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+ | 0.3327 | 11.0 | 132 | 0.3054 | 0.6957 | 0.7848 | 0.2 |
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+ | 0.3206 | 12.0 | 144 | 0.2998 | 0.7297 | 0.8156 | 0.2 |
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+ | 0.3125 | 13.0 | 156 | 0.2926 | 0.7222 | 0.8066 | 0.2 |
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+ | 0.3073 | 14.0 | 168 | 0.2847 | 0.7671 | 0.8361 | 0.3 |
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+ | 0.2972 | 15.0 | 180 | 0.2819 | 0.7606 | 0.8271 | 0.3 |
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+ | 0.2933 | 16.0 | 192 | 0.2773 | 0.7606 | 0.8271 | 0.3 |
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+ | 0.2798 | 17.0 | 204 | 0.2752 | 0.7606 | 0.8271 | 0.3 |
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+ | 0.2737 | 18.0 | 216 | 0.2731 | 0.7606 | 0.8271 | 0.3 |
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+ | 0.2866 | 19.0 | 228 | 0.2720 | 0.7606 | 0.8271 | 0.3 |
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+ | 0.2729 | 20.0 | 240 | 0.2713 | 0.7606 | 0.8271 | 0.3 |
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  ### Framework versions