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wav2vec2-base-finetuned-common_voice

Audio Classification
Transformers
TensorBoard
Safetensors
wav2vec2
Generated from Trainer
Inference Endpoints
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  1. README.md +17 -17
  2. model.safetensors +1 -1
README.md CHANGED
@@ -20,13 +20,13 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0419
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- - Accuracy: 0.995
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- - F1: 0.9950
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- - Recall: 0.9950
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- - Precision: 0.9951
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- - Mcc: 0.9938
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- - Auc: 0.9987
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  ## Model description
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@@ -59,16 +59,16 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision | Mcc | Auc |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|:------:|:------:|
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- | 0.8258 | 1.0 | 200 | 0.7423 | 0.76 | 0.6973 | 0.76 | 0.6699 | 0.7402 | 0.9766 |
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- | 0.1609 | 2.0 | 400 | 0.1559 | 0.96 | 0.9596 | 0.96 | 0.9644 | 0.9513 | 0.9997 |
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- | 0.219 | 3.0 | 600 | 0.0864 | 0.9825 | 0.9826 | 0.9825 | 0.9828 | 0.9782 | 0.9983 |
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- | 0.0049 | 4.0 | 800 | 0.0341 | 0.995 | 0.9950 | 0.9950 | 0.9950 | 0.9938 | 0.9999 |
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- | 0.0031 | 5.0 | 1000 | 0.1241 | 0.98 | 0.9799 | 0.9800 | 0.9808 | 0.9752 | 0.9989 |
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- | 0.0021 | 6.0 | 1200 | 0.0394 | 0.995 | 0.9950 | 0.9950 | 0.9951 | 0.9938 | 0.9988 |
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- | 0.0017 | 7.0 | 1400 | 0.0410 | 0.995 | 0.9950 | 0.9950 | 0.9951 | 0.9938 | 0.9993 |
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- | 0.0015 | 8.0 | 1600 | 0.0420 | 0.995 | 0.9950 | 0.9950 | 0.9951 | 0.9938 | 0.9987 |
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- | 0.0013 | 9.0 | 1800 | 0.0418 | 0.995 | 0.9950 | 0.9950 | 0.9951 | 0.9938 | 0.9987 |
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- | 0.0013 | 10.0 | 2000 | 0.0419 | 0.995 | 0.9950 | 0.9950 | 0.9951 | 0.9938 | 0.9987 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0002
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+ - Accuracy: 1.0
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+ - F1: 1.0
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+ - Recall: 1.0
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+ - Precision: 1.0
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+ - Mcc: 1.0
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+ - Auc: 1.0
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision | Mcc | Auc |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|:------:|:------:|
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+ | 0.3184 | 1.0 | 200 | 0.2012 | 0.97 | 0.9693 | 0.97 | 0.9721 | 0.9633 | 0.9965 |
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+ | 0.0889 | 2.0 | 400 | 0.0144 | 0.995 | 0.9950 | 0.9950 | 0.9950 | 0.9938 | 1.0000 |
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+ | 0.1011 | 3.0 | 600 | 0.0482 | 0.9925 | 0.9925 | 0.9925 | 0.9928 | 0.9907 | 0.9987 |
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+ | 0.0007 | 4.0 | 800 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | 0.0005 | 5.0 | 1000 | 0.0003 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | 0.0003 | 6.0 | 1200 | 0.0003 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | 0.0004 | 7.0 | 1400 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | 0.0003 | 8.0 | 1600 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | 0.0003 | 9.0 | 1800 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | 0.0002 | 10.0 | 2000 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
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  ### Framework versions
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