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unispeech-sat-base-finetuned-common_voice

Audio Classification
Transformers
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Safetensors
unispeech-sat
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  1. README.md +17 -17
  2. model.safetensors +1 -1
README.md CHANGED
@@ -19,13 +19,13 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [microsoft/unispeech-sat-base](https://huggingface.co/microsoft/unispeech-sat-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0481
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- - Accuracy: 0.9925
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- - F1: 0.9925
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- - Recall: 0.9925
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- - Precision: 0.9928
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- - Mcc: 0.9907
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- - Auc: 0.9999
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  ## Model description
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@@ -60,16 +60,16 @@ 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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- | 1.5302 | 1.0 | 50 | 1.4495 | 0.56 | 0.5047 | 0.5600 | 0.6655 | 0.4723 | 0.8635 |
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- | 1.1592 | 2.0 | 100 | 0.9831 | 0.7125 | 0.6783 | 0.7125 | 0.7985 | 0.6723 | 0.9633 |
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- | 0.7313 | 3.0 | 150 | 0.5535 | 0.9425 | 0.9428 | 0.9425 | 0.9455 | 0.9287 | 0.9926 |
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- | 0.4431 | 4.0 | 200 | 0.2633 | 0.965 | 0.9651 | 0.9650 | 0.9676 | 0.9569 | 0.9976 |
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- | 0.2353 | 5.0 | 250 | 0.1310 | 0.985 | 0.9850 | 0.985 | 0.9856 | 0.9814 | 0.9998 |
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- | 0.1846 | 6.0 | 300 | 0.1136 | 0.9775 | 0.9775 | 0.9775 | 0.9783 | 0.9721 | 0.9978 |
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- | 0.1464 | 7.0 | 350 | 0.0714 | 0.9875 | 0.9875 | 0.9875 | 0.9878 | 0.9844 | 1.0000 |
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- | 0.1016 | 8.0 | 400 | 0.0592 | 0.99 | 0.9900 | 0.99 | 0.9902 | 0.9876 | 0.9999 |
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- | 0.057 | 9.0 | 450 | 0.0466 | 0.9925 | 0.9925 | 0.9925 | 0.9928 | 0.9907 | 0.9999 |
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- | 0.068 | 10.0 | 500 | 0.0481 | 0.9925 | 0.9925 | 0.9925 | 0.9928 | 0.9907 | 0.9999 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [microsoft/unispeech-sat-base](https://huggingface.co/microsoft/unispeech-sat-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0013
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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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+ | 0.1326 | 1.0 | 50 | 0.0283 | 0.9975 | 0.9975 | 0.9975 | 0.9975 | 0.9969 | 1.0 |
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+ | 0.1323 | 2.0 | 100 | 0.0450 | 0.9925 | 0.9925 | 0.9925 | 0.9928 | 0.9907 | 0.9994 |
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+ | 0.0499 | 3.0 | 150 | 0.0081 | 0.9975 | 0.9975 | 0.9975 | 0.9975 | 0.9969 | 1.0 |
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+ | 0.0183 | 4.0 | 200 | 0.0037 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | 0.024 | 5.0 | 250 | 0.0026 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | 0.0326 | 6.0 | 300 | 0.0020 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | 0.0172 | 7.0 | 350 | 0.0017 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | 0.0053 | 8.0 | 400 | 0.0015 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | 0.0034 | 9.0 | 450 | 0.0050 | 0.9975 | 0.9975 | 0.9975 | 0.9975 | 0.9969 | 1.0 |
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+ | 0.014 | 10.0 | 500 | 0.0013 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
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  ### Framework versions
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