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Kylam13
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my_fyp_test13

Audio Classification
Transformers
TensorBoard
Safetensors
wav2vec2
Generated from Trainer
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xet
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End of training

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  1. README.md +28 -28
  2. model.safetensors +1 -1
README.md CHANGED
@@ -18,8 +18,8 @@ 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: 2.7737
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- - Accuracy: 0.2475
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  ## Model description
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@@ -53,32 +53,32 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 1.0 | 7 | 3.8284 | 0.0663 |
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- | 3.5661 | 2.0 | 14 | 3.6576 | 0.06 |
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- | 3.3789 | 3.0 | 21 | 3.5513 | 0.065 |
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- | 3.3789 | 4.0 | 28 | 3.4661 | 0.065 |
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- | 2.9843 | 5.0 | 35 | 3.3844 | 0.065 |
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- | 3.135 | 6.0 | 42 | 3.3062 | 0.065 |
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- | 3.135 | 7.0 | 49 | 3.2334 | 0.065 |
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- | 2.7869 | 8.0 | 56 | 3.1669 | 0.0963 |
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- | 2.94 | 9.0 | 63 | 3.1070 | 0.1013 |
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- | 2.6278 | 10.0 | 70 | 3.0550 | 0.1163 |
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- | 2.6278 | 11.0 | 77 | 3.0117 | 0.1388 |
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- | 2.7834 | 12.0 | 84 | 2.9683 | 0.1525 |
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- | 2.7128 | 13.0 | 91 | 2.9132 | 0.1913 |
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- | 2.7128 | 14.0 | 98 | 2.8913 | 0.2112 |
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- | 2.4452 | 15.0 | 105 | 2.8593 | 0.2188 |
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- | 2.6093 | 16.0 | 112 | 2.8393 | 0.2225 |
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- | 2.6093 | 17.0 | 119 | 2.8211 | 0.2375 |
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- | 2.3635 | 18.0 | 126 | 2.8111 | 0.2288 |
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- | 2.5329 | 19.0 | 133 | 2.7953 | 0.2425 |
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- | 2.3088 | 20.0 | 140 | 2.7871 | 0.25 |
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- | 2.3088 | 21.0 | 147 | 2.7805 | 0.2525 |
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- | 2.4873 | 22.0 | 154 | 2.7780 | 0.2487 |
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- | 2.4754 | 23.0 | 161 | 2.7742 | 0.2487 |
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- | 2.4754 | 24.0 | 168 | 2.7741 | 0.25 |
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- | 2.2766 | 25.0 | 175 | 2.7737 | 0.2475 |
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- | 2.4643 | 25.8 | 180 | 2.7737 | 0.2475 |
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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: 2.8594
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+ - Accuracy: 0.17
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 7 | 3.8041 | 0.0638 |
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+ | 3.5516 | 2.0 | 14 | 3.5967 | 0.0625 |
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+ | 3.329 | 3.0 | 21 | 3.4894 | 0.0625 |
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+ | 3.329 | 4.0 | 28 | 3.4042 | 0.07 |
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+ | 2.9364 | 5.0 | 35 | 3.3234 | 0.065 |
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+ | 3.0836 | 6.0 | 42 | 3.2488 | 0.07 |
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+ | 3.0836 | 7.0 | 49 | 3.1819 | 0.07 |
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+ | 2.7451 | 8.0 | 56 | 3.1250 | 0.07 |
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+ | 2.8969 | 9.0 | 63 | 3.0800 | 0.07 |
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+ | 2.6078 | 10.0 | 70 | 3.0414 | 0.07 |
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+ | 2.6078 | 11.0 | 77 | 3.0133 | 0.0838 |
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+ | 2.7883 | 12.0 | 84 | 2.9887 | 0.0963 |
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+ | 2.7495 | 13.0 | 91 | 2.9683 | 0.105 |
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+ | 2.7495 | 14.0 | 98 | 2.9482 | 0.13 |
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+ | 2.4974 | 15.0 | 105 | 2.9343 | 0.1237 |
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+ | 2.6843 | 16.0 | 112 | 2.9164 | 0.135 |
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+ | 2.6843 | 17.0 | 119 | 2.9068 | 0.145 |
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+ | 2.4408 | 18.0 | 126 | 2.8867 | 0.16 |
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+ | 2.6254 | 19.0 | 133 | 2.8676 | 0.1675 |
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+ | 2.4018 | 20.0 | 140 | 2.8673 | 0.1737 |
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+ | 2.4018 | 21.0 | 147 | 2.8651 | 0.1713 |
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+ | 2.5887 | 22.0 | 154 | 2.8591 | 0.1688 |
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+ | 2.5823 | 23.0 | 161 | 2.8593 | 0.1725 |
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+ | 2.5823 | 24.0 | 168 | 2.8578 | 0.1675 |
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+ | 2.3684 | 25.0 | 175 | 2.8593 | 0.1713 |
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+ | 2.571 | 25.8 | 180 | 2.8594 | 0.17 |
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  ### Framework versions
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