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Eappelson
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misdirection_classification

Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
Inference Endpoints
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  1. README.md +19 -14
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -20,12 +20,12 @@ 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: 0.6617
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- - Accuracy: 0.6506
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- - Precision: 0.6461
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- - Recall: 0.6506
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- - F1: 0.6404
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- - Roc Auc: 0.6614
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  ## Model description
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@@ -44,7 +44,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 3.878471195998478e-05
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
@@ -52,16 +52,21 @@ The following hyperparameters were used during training:
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  - total_train_batch_size: 16
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 4
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Roc Auc |
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- |:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:|
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- | 0.6731 | 0.9796 | 24 | 0.6465 | 0.6145 | 0.6271 | 0.6145 | 0.5549 | 0.6718 |
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- | 0.6435 | 2.0 | 49 | 0.6477 | 0.6325 | 0.6576 | 0.6325 | 0.5781 | 0.6540 |
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- | 0.5115 | 2.9796 | 73 | 0.6617 | 0.6506 | 0.6461 | 0.6506 | 0.6404 | 0.6614 |
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- | 0.4314 | 3.9184 | 96 | 0.6791 | 0.6446 | 0.6480 | 0.6446 | 0.6171 | 0.6573 |
 
 
 
 
 
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  ### Framework versions
 
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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: 0.9041
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+ - Accuracy: 0.6937
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+ - Precision: 0.6959
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+ - Recall: 0.6937
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+ - F1: 0.6829
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+ - Roc Auc: 0.6835
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 4.890081827045594e-05
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
 
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  - total_train_batch_size: 16
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - num_epochs: 9
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Roc Auc |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:|
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+ | 0.6496 | 1.0 | 28 | 0.6713 | 0.6216 | 0.6683 | 0.6216 | 0.5502 | 0.6567 |
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+ | 0.4718 | 2.0 | 56 | 0.7125 | 0.6486 | 0.6463 | 0.6486 | 0.6348 | 0.6667 |
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+ | 0.2081 | 3.0 | 84 | 0.9041 | 0.6937 | 0.6959 | 0.6937 | 0.6829 | 0.6835 |
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+ | 0.1064 | 4.0 | 112 | 1.1360 | 0.6667 | 0.6720 | 0.6667 | 0.6474 | 0.6928 |
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+ | 0.0202 | 5.0 | 140 | 1.1922 | 0.6577 | 0.6543 | 0.6577 | 0.6540 | 0.6928 |
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+ | 0.1239 | 6.0 | 168 | 1.4047 | 0.6667 | 0.6690 | 0.6667 | 0.6506 | 0.6753 |
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+ | 0.074 | 7.0 | 196 | 1.3902 | 0.6486 | 0.6448 | 0.6486 | 0.6441 | 0.6683 |
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+ | 0.0738 | 8.0 | 224 | 1.4045 | 0.6486 | 0.6478 | 0.6486 | 0.6482 | 0.6650 |
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+ | 0.0458 | 9.0 | 252 | 1.4082 | 0.6306 | 0.6316 | 0.6306 | 0.6311 | 0.6634 |
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  ### Framework versions
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