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ajrayman
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psychopathy_binary

Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
Inference Endpoints
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ajrayman commited on
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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: psychopathy_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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- # psychopathy_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: 0.5940
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- - Accuracy: 0.7207
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- - Precision: 0.7847
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- - Recall: 0.6232
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- - F1: 0.6947
 
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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 | 0.6312 | 0.6317 | 0.8995 | 0.3125 | 0.4638 |
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- | No log | 2.0 | 268 | 0.5610 | 0.7001 | 0.7074 | 0.7022 | 0.7048 |
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- | No log | 3.0 | 402 | 0.5940 | 0.7207 | 0.7847 | 0.6232 | 0.6947 |
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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: machiavellianism_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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+ # machiavellianism_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: 0.6395
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+ - Accuracy: 0.6857
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+ - Precision: 0.6961
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+ - Recall: 0.6445
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+ - F1: 0.6693
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+ - Auc: 0.6852
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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 | 0.6680 | 0.6388 | 0.9075 | 0.2985 | 0.4492 | 0.6344 |
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+ | No log | 2.0 | 268 | 0.5901 | 0.6867 | 0.7963 | 0.4905 | 0.6071 | 0.6841 |
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+ | No log | 3.0 | 402 | 0.6395 | 0.6857 | 0.6961 | 0.6445 | 0.6693 | 0.6852 |
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  ### Framework versions
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