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ajrayman
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Liberalism_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: Liberalism_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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- # Liberalism_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: 0.6782
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- - Precision: 0.6618
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- - Recall: 0.6960
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- - F1: 0.6785
 
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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 | 0.6187 | 0.6371 | 0.7463 | 0.3881 | 0.5107 |
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- | No log | 2.0 | 268 | 0.6014 | 0.6763 | 0.6588 | 0.6979 | 0.6778 |
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- | No log | 3.0 | 402 | 0.6927 | 0.6782 | 0.6618 | 0.6960 | 0.6785 |
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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: Intellect_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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+ # Intellect_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: 0.6577
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+ - Accuracy: 0.6511
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+ - Precision: 0.6853
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+ - Recall: 0.5685
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+ - F1: 0.6215
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+ - Auc: 0.6517
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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 | 0.6308 | 0.6614 | 0.6539 | 0.6963 | 0.6744 | 0.6611 |
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+ | No log | 2.0 | 268 | 0.6236 | 0.6539 | 0.7086 | 0.5315 | 0.6074 | 0.6548 |
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+ | No log | 3.0 | 402 | 0.6577 | 0.6511 | 0.6853 | 0.5685 | 0.6215 | 0.6517 |
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  ### Framework versions
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