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README.md
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This is to deplicate the work of
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[wav2vec2-base-Speech_Emotion_Recognition](https://huggingface.co/DunnBC22/wav2vec2-base-Speech_Emotion_Recognition)
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*Only little changes are made for success run on google colab.*
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### My Version of metrics:
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|Epoch |Training Loss |Validation Loss |Accuracy |Weighted f1 |Micro f1 |Macro f1 |Weighted recall |Micro recall |Macro recall |Weighted precision |Micro precision |Macro precision
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| ----|----|----|----|----|----|----|----|----|----|----|----|----|
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|0 | 1.789200 | 1.548816 | 0.382590 | 0.287415 | 0.382590 | 0.289045 | 0.382590 | 0.382590 | 0.379768 | 0.473585 | 0.382590 | 0.467116 |
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|1 | 1.789200 | 1.302810 | 0.529823 | 0.511868 | 0.529823 | 0.511619 | 0.529823 | 0.529823 | 0.523766 | 0.552868 | 0.529823 | 0.560496 |
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|2 | 1.789200 | 1.029921 | 0.672757 | 0.668108 | 0.672757 | 0.669246 | 0.672757 | 0.672757 | 0.676383 | 0.674857 | 0.672757 | 0.673698 |
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|3 | 1.789200 | 0.968154 | 0.677055 | 0.671986 | 0.677055 | 0.674074 | 0.677055 | 0.677055 | 0.676891 | 0.701300 | 0.677055 | 0.705734 |
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|4 | 1.789200 | 0.850912 | 0.717894 | 0.714321 | 0.717894 | 0.716527 | 0.717894 | 0.717894 | 0.722476 | 0.716772 | 0.717894 | 0.716698 |
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|5 | 1.789200 | 0.870916 | 0.710371 | 0.706013 | 0.710371 | 0.708563 | 0.710371 | 0.710371 | 0.713853 | 0.710966 | 0.710371 | 0.712245 |
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|6 | 1.789200 | 0.827148 | 0.729178 | 0.725336 | 0.729178 | 0.726744 | 0.729178 | 0.729178 | 0.732127 | 0.735935 | 0.729178 | 0.736041 |
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|7 | 1.789200 | 0.798354 | 0.729715 | 0.727086 | 0.729715 | 0.728847 | 0.729715 | 0.729715 | 0.732476 | 0.729932 | 0.729715 | 0.730688 |
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|8 | 1.789200 | 0.799373 | 0.735626 | 0.732981 | 0.735626 | 0.735058 | 0.735626 | 0.735626 | 0.738147 | 0.741482 | 0.735626 | 0.742782 |
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|9 | 1.789200 | 0.810692 | 0.728103 | 0.724754 | 0.728103 | 0.726852 | 0.728103 | 0.728103 | 0.731083 | 0.731919 | 0.728103 | 0.732869 |
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```***** Running Evaluation *****
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Num examples = 1861 Batch size = 32 [59/59 08:38]
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{'eval_loss': 0.8106924891471863,
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'eval_accuracy': 0.7281031703385277,
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'eval_Weighted F1': 0.7247543780750472,
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'eval_Micro F1': 0.7281031703385277,
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'eval_Macro F1': 0.7268519957485492,
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'eval_Weighted Recall': 0.7281031703385277,
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'eval_Micro Recall': 0.7281031703385277,
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'eval_Macro Recall': 0.7310833557439055,
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'eval_Weighted Precision': 0.7319188411210771,
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'eval_Micro Precision': 0.7281031703385277,
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'eval_Macro Precision': 0.732869407033253,
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'eval_runtime': 83.3066,
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'eval_samples_per_second': 22.339,
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'eval_steps_per_second': 0.708,
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'epoch': 9.98}
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```
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### Model description
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This model predicts the emotion of the person speaking in the audio sample.
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For more information on how it was created, check out the following link: https://github.com/DunnBC22/Vision_Audio_and_Multimodal_Projects/tree/main/Audio-Projects/Emotion%20Detection/Speech%20Emotion%20Detection
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### Training and evaluation data
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Dataset Source: https://www.kaggle.com/datasets/dmitrybabko/speech-emotion-recognition-en
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