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End of training

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  1. README.md +8 -8
  2. model.safetensors +1 -1
README.md CHANGED
@@ -5,21 +5,21 @@ base_model: roberta-large
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  tags:
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  - generated_from_trainer
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  model-index:
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- - name: Depression_continuous
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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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- # Depression_continuous
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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: 0.0762
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- - Rmse: 0.2761
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- - Mae: 0.2271
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- - Corr: 0.4709
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  ## Model description
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@@ -50,8 +50,8 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Rmse | Mae | Corr |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|
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- | No log | 1.0 | 268 | 0.0730 | 0.2702 | 0.2237 | 0.4235 |
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- | 0.0925 | 2.0 | 536 | 0.0762 | 0.2761 | 0.2271 | 0.4709 |
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  ### Framework versions
 
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  tags:
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  - generated_from_trainer
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  model-index:
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+ - name: Self-consciousness_continuous
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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-consciousness_continuous
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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: 0.0414
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+ - Rmse: 0.2034
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+ - Mae: 0.1638
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+ - Corr: 0.2866
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Rmse | Mae | Corr |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|
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+ | No log | 1.0 | 268 | 0.0427 | 0.2067 | 0.1669 | 0.2611 |
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+ | 0.0634 | 2.0 | 536 | 0.0414 | 0.2034 | 0.1638 | 0.2866 |
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  ### Framework versions
model.safetensors CHANGED
@@ -1,3 +1,3 @@
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  size 1421491316
 
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