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End of training

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README.md CHANGED
@@ -20,12 +20,12 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 3.2561
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- - Accuracy: 0.2155
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- - Precision: 0.1870
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- - Recall: 0.2155
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- - F1: 0.1453
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- - Binary: 0.4380
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  ## Model description
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@@ -44,7 +44,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 3e-05
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  - train_batch_size: 32
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  - eval_batch_size: 32
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  - seed: 42
@@ -59,17 +59,16 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Binary |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
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- | No log | 0.86 | 50 | 4.2865 | 0.0291 | 0.0034 | 0.0291 | 0.0043 | 0.2661 |
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- | No log | 1.72 | 100 | 4.0141 | 0.0460 | 0.0306 | 0.0460 | 0.0187 | 0.3199 |
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- | No log | 2.59 | 150 | 3.8172 | 0.0630 | 0.0204 | 0.0630 | 0.0214 | 0.3378 |
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- | No log | 3.45 | 200 | 3.7045 | 0.0896 | 0.0534 | 0.0896 | 0.0533 | 0.3431 |
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- | No log | 4.31 | 250 | 3.5695 | 0.1308 | 0.0844 | 0.1308 | 0.0796 | 0.3785 |
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- | No log | 5.17 | 300 | 3.4883 | 0.1622 | 0.1140 | 0.1622 | 0.1002 | 0.3954 |
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- | No log | 6.03 | 350 | 3.4447 | 0.1622 | 0.1145 | 0.1622 | 0.1005 | 0.3925 |
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- | No log | 6.9 | 400 | 3.3482 | 0.1671 | 0.0972 | 0.1671 | 0.1026 | 0.4077 |
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- | No log | 7.76 | 450 | 3.3042 | 0.1961 | 0.1424 | 0.1961 | 0.1295 | 0.4228 |
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- | 3.7796 | 8.62 | 500 | 3.2724 | 0.2131 | 0.1898 | 0.2131 | 0.1472 | 0.4370 |
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- | 3.7796 | 9.48 | 550 | 3.2561 | 0.2155 | 0.1870 | 0.2155 | 0.1453 | 0.4380 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 3.9330
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+ - Accuracy: 0.0674
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+ - Precision: 0.0116
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+ - Recall: 0.0674
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+ - F1: 0.0182
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+ - Binary: 0.3423
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 1e-05
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  - train_batch_size: 32
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  - eval_batch_size: 32
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Binary |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
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+ | No log | 0.96 | 50 | 4.4099 | 0.0647 | 0.0191 | 0.0647 | 0.0221 | 0.2396 |
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+ | No log | 1.91 | 100 | 4.3523 | 0.0593 | 0.0190 | 0.0593 | 0.0194 | 0.3019 |
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+ | No log | 2.87 | 150 | 4.2416 | 0.0701 | 0.0246 | 0.0701 | 0.0235 | 0.3358 |
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+ | No log | 3.83 | 200 | 4.1412 | 0.0701 | 0.0265 | 0.0701 | 0.0214 | 0.3437 |
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+ | No log | 4.78 | 250 | 4.0716 | 0.0593 | 0.0069 | 0.0593 | 0.0122 | 0.3334 |
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+ | No log | 5.74 | 300 | 4.0195 | 0.0701 | 0.0124 | 0.0701 | 0.0186 | 0.3453 |
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+ | No log | 6.7 | 350 | 3.9850 | 0.0593 | 0.0073 | 0.0593 | 0.0126 | 0.3350 |
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+ | No log | 7.66 | 400 | 3.9610 | 0.0647 | 0.0097 | 0.0647 | 0.0162 | 0.3388 |
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+ | No log | 8.61 | 450 | 3.9420 | 0.0674 | 0.0113 | 0.0674 | 0.0180 | 0.3396 |
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+ | 4.2019 | 9.57 | 500 | 3.9330 | 0.0674 | 0.0116 | 0.0674 | 0.0182 | 0.3423 |
 
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  ### Framework versions
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