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End of training

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README.md CHANGED
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  ---
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  license: mit
 
 
 
 
 
 
 
 
 
 
 
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  license: mit
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+ base_model: roberta-base
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ - f1
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+ - precision
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+ - recall
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+ model-index:
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+ - name: roberta-base_stress_classification
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+ results: []
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  ---
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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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+
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+ # roberta-base_stress_classification
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+
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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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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 500
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+ - num_epochs: 5
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+
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+ ### Training results
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+
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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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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.0
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