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Anxiety_binary

Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
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Training in progress, epoch 1

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  1. README.md +13 -12
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -10,22 +10,23 @@ metrics:
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  - recall
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  - f1
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  model-index:
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- - name: Anxiety_binary
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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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  should probably proofread and complete it, then remove this comment. -->
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- # Anxiety_binary
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  This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5851
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- - Accuracy: 0.6847
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- - Precision: 0.6898
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- - Recall: 0.6450
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- - F1: 0.6667
 
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  ## Model description
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@@ -54,11 +55,11 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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- | No log | 1.0 | 134 | 0.6335 | 0.6660 | 0.7139 | 0.5286 | 0.6075 |
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- | No log | 2.0 | 268 | 0.6254 | 0.6735 | 0.6330 | 0.7901 | 0.7029 |
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- | No log | 3.0 | 402 | 0.5851 | 0.6847 | 0.6898 | 0.6450 | 0.6667 |
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  ### Framework versions
 
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  - recall
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  - f1
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  model-index:
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+ - name: PuritySanctity_binary
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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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  should probably proofread and complete it, then remove this comment. -->
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+ # PuritySanctity_binary
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  This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6174
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+ - Accuracy: 0.6904
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+ - Precision: 0.6805
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+ - Recall: 0.7273
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+ - F1: 0.7031
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+ - Auc: 0.6901
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  ## Model description
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Auc |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
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+ | No log | 1.0 | 123 | 0.6316 | 0.6548 | 0.6182 | 0.8242 | 0.7065 | 0.6534 |
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+ | No log | 2.0 | 246 | 0.6060 | 0.6843 | 0.6782 | 0.7111 | 0.6943 | 0.6841 |
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+ | No log | 3.0 | 369 | 0.6174 | 0.6904 | 0.6805 | 0.7273 | 0.7031 | 0.6901 |
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  ### Framework versions
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