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text finetuning on full dataset with validation set

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  1. README.md +17 -20
  2. model.safetensors +1 -1
README.md CHANGED
@@ -11,9 +11,6 @@ metrics:
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  model-index:
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  - name: DL_Audio_Hatespeech_text_classification_trainer_push
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  results: []
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- widget:
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- - text: It is crazy how diverse certain schools are!
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- - text: I hate sleeping in!
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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
@@ -23,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.6725
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- - Accuracy: 0.7641
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- - Recall: 0.7771
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- - Precision: 0.7620
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- - F1: 0.7695
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  ## Model description
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@@ -59,18 +56,18 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | Precision | F1 |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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- | 0.0191 | 1.0 | 97 | 1.5765 | 0.7483 | 0.8032 | 0.7281 | 0.7638 |
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- | 0.0351 | 2.0 | 194 | 1.2599 | 0.7428 | 0.8070 | 0.7195 | 0.7607 |
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- | 0.0451 | 3.0 | 291 | 1.1736 | 0.7580 | 0.7860 | 0.7488 | 0.7669 |
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- | 0.039 | 4.0 | 388 | 1.2600 | 0.7557 | 0.7592 | 0.7588 | 0.7590 |
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- | 0.039 | 5.0 | 485 | 1.1336 | 0.7606 | 0.7631 | 0.7640 | 0.7635 |
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- | 0.0199 | 6.0 | 582 | 1.4645 | 0.7593 | 0.7777 | 0.7546 | 0.7660 |
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- | 0.017 | 7.0 | 679 | 1.5825 | 0.7628 | 0.7096 | 0.7997 | 0.7519 |
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- | 0.0062 | 8.0 | 776 | 1.5688 | 0.7673 | 0.7510 | 0.7813 | 0.7658 |
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- | 0.0121 | 9.0 | 873 | 1.6285 | 0.7651 | 0.7510 | 0.7777 | 0.7641 |
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- | 0.0054 | 10.0 | 970 | 1.6725 | 0.7641 | 0.7771 | 0.7620 | 0.7695 |
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  ### Framework versions
 
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  model-index:
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  - name: DL_Audio_Hatespeech_text_classification_trainer_push
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  results: []
 
 
 
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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 [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.0640
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+ - Accuracy: 0.7544
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+ - Recall: 0.7930
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+ - Precision: 0.7406
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+ - F1: 0.7659
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  ## Model description
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | Precision | F1 |
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+ |:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | 0.4863 | 0.9935 | 77 | 0.4678 | 0.7701 | 0.7421 | 0.7841 | 0.7625 |
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+ | 0.3935 | 2.0 | 155 | 0.4595 | 0.7834 | 0.7340 | 0.8124 | 0.7712 |
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+ | 0.2792 | 2.9935 | 232 | 0.5285 | 0.7850 | 0.7291 | 0.8188 | 0.7713 |
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+ | 0.1408 | 4.0 | 310 | 0.7130 | 0.7785 | 0.7940 | 0.7684 | 0.7810 |
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+ | 0.0945 | 4.9935 | 387 | 0.8230 | 0.7806 | 0.7551 | 0.7937 | 0.7739 |
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+ | 0.0541 | 6.0 | 465 | 0.9977 | 0.7737 | 0.8118 | 0.7526 | 0.7811 |
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+ | 0.0331 | 6.9935 | 542 | 1.1107 | 0.7753 | 0.7859 | 0.7678 | 0.7768 |
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+ | 0.0151 | 8.0 | 620 | 1.1703 | 0.7789 | 0.7543 | 0.7915 | 0.7724 |
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+ | 0.0106 | 8.9935 | 697 | 1.2741 | 0.7785 | 0.7616 | 0.7864 | 0.7738 |
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+ | 0.0051 | 9.9355 | 770 | 1.2964 | 0.7753 | 0.7851 | 0.7683 | 0.7766 |
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  ### Framework versions
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