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roberta-base_stress_classification

Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
roberta
stress
classification
glassdoor
Eval Results
Inference Endpoints
Model card Files Metrics Community
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End of training

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  1. README.md +10 -10
  2. logs/events.out.tfevents.1706089146.3ba10b00d69f.392.2 +2 -2
  3. logs/events.out.tfevents.1706089895.3ba10b00d69f.392.3 +3 -0
README.md CHANGED
@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0642
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- - Accuracy: 0.9844
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- - F1: 0.9844
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- - Precision: 0.9848
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- - Recall: 0.9844
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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- | 0.3508 | 1.0 | 160 | 0.2642 | 0.9031 | 0.9027 | 0.9102 | 0.9031 |
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- | 0.4855 | 2.0 | 320 | 0.1365 | 0.975 | 0.9750 | 0.9751 | 0.975 |
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- | 0.0655 | 3.0 | 480 | 0.0642 | 0.9844 | 0.9844 | 0.9848 | 0.9844 |
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- | 0.0884 | 4.0 | 640 | 0.0699 | 0.9875 | 0.9875 | 0.9878 | 0.9875 |
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- | 0.0006 | 5.0 | 800 | 0.0741 | 0.9844 | 0.9844 | 0.9845 | 0.9844 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0389
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+ - Accuracy: 0.9938
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+ - F1: 0.9938
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+ - Precision: 0.9938
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+ - Recall: 0.9938
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | 0.2345 | 1.0 | 160 | 0.1980 | 0.9437 | 0.9437 | 0.9449 | 0.9437 |
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+ | 0.2676 | 2.0 | 320 | 0.1086 | 0.9844 | 0.9844 | 0.9848 | 0.9844 |
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+ | 0.0393 | 3.0 | 480 | 0.1011 | 0.9812 | 0.9812 | 0.9816 | 0.9812 |
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+ | 0.1025 | 4.0 | 640 | 0.0389 | 0.9938 | 0.9938 | 0.9938 | 0.9938 |
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+ | 0.0004 | 5.0 | 800 | 0.0654 | 0.9875 | 0.9875 | 0.9876 | 0.9875 |
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  ### Framework versions
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