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IngroupLoyalty_binary

Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
Inference Endpoints
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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: IngroupLoyalty_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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- # IngroupLoyalty_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: 0.6927
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- - Accuracy: 0.6690
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- - Precision: 0.6752
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- - Recall: 0.7010
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- - F1: 0.6879
 
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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 | 127 | 0.6813 | 0.6601 | 0.7333 | 0.5448 | 0.6251 |
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- | No log | 2.0 | 254 | 0.6369 | 0.6868 | 0.6683 | 0.7905 | 0.7243 |
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- | No log | 3.0 | 381 | 0.6927 | 0.6690 | 0.6752 | 0.7010 | 0.6879 |
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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: FairnessReciprocity_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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+ # FairnessReciprocity_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: 0.6999
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+ - Accuracy: 0.5972
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+ - Precision: 0.5651
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+ - Recall: 0.6674
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+ - F1: 0.6120
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+ - Auc: 0.6004
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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 | 125 | 0.6727 | 0.5782 | 0.5754 | 0.4337 | 0.4946 | 0.5715 |
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+ | No log | 2.0 | 250 | 0.6749 | 0.5912 | 0.5579 | 0.68 | 0.6129 | 0.5953 |
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+ | No log | 3.0 | 375 | 0.6999 | 0.5972 | 0.5651 | 0.6674 | 0.6120 | 0.6004 |
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  ### Framework versions
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