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Excitement_Seeking_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: Excitement_Seeking_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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- # Excitement_Seeking_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: 0.6047
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- - Accuracy: 0.6887
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- - Precision: 0.7024
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- - Recall: 0.7148
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- - F1: 0.7086
 
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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 | 0.6683 | 0.5993 | 0.7396 | 0.375 | 0.4977 |
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- | No log | 2.0 | 268 | 0.6426 | 0.6226 | 0.7447 | 0.4366 | 0.5505 |
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- | No log | 3.0 | 402 | 0.6047 | 0.6887 | 0.7024 | 0.7148 | 0.7086 |
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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: Activity_Level_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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+ # Activity_Level_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: 0.6988
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+ - Accuracy: 0.6138
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+ - Precision: 0.638
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+ - Recall: 0.5779
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+ - F1: 0.6065
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+ - Auc: 0.6149
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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 | 0.6591 | 0.6073 | 0.6520 | 0.5091 | 0.5717 | 0.6103 |
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+ | No log | 2.0 | 268 | 0.6495 | 0.6175 | 0.6511 | 0.5543 | 0.5988 | 0.6195 |
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+ | No log | 3.0 | 402 | 0.6988 | 0.6138 | 0.638 | 0.5779 | 0.6065 | 0.6149 |
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  ### Framework versions
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