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Self_Efficacy_binary

Text Classification
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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: Self_Efficacy_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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- # Self_Efficacy_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: 0.6822
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- - Accuracy: 0.6468
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- - Precision: 0.6816
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- - Recall: 0.5996
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- - F1: 0.6380
 
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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 | 0.6634 | 0.6132 | 0.6849 | 0.4722 | 0.5590 |
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- | No log | 2.0 | 268 | 0.6410 | 0.6393 | 0.6714 | 0.5978 | 0.6325 |
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- | No log | 3.0 | 402 | 0.6822 | 0.6468 | 0.6816 | 0.5996 | 0.6380 |
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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: Sympathy_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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+ # Sympathy_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: 0.6330
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+ - Accuracy: 0.6688
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+ - Precision: 0.6621
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+ - Recall: 0.7072
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+ - F1: 0.6839
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+ - Auc: 0.6683
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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 | 134 | 0.6460 | 0.6119 | 0.6779 | 0.4457 | 0.5378 | 0.6141 |
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+ | No log | 2.0 | 268 | 0.6462 | 0.6465 | 0.6277 | 0.7422 | 0.6802 | 0.6452 |
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+ | No log | 3.0 | 402 | 0.6330 | 0.6688 | 0.6621 | 0.7072 | 0.6839 | 0.6683 |
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  ### Framework versions
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