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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: 3.2824
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- - Accuracy: 0.1864
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- - Precision: 0.1087
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- - Recall: 0.1864
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- - F1: 0.1114
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- - Binary: 0.4189
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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 +59,17 @@ 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 | 4.2455 | 0.0533 | 0.0410 | 0.0533 | 0.0255 | 0.3252 |
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- | No log | 1.72 | 100 | 3.9851 | 0.0630 | 0.0179 | 0.0630 | 0.0163 | 0.3249 |
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- | No log | 2.59 | 150 | 3.7681 | 0.0726 | 0.0401 | 0.0726 | 0.0283 | 0.3421 |
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- | No log | 3.45 | 200 | 3.7448 | 0.0678 | 0.0383 | 0.0678 | 0.0252 | 0.3167 |
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- | No log | 4.31 | 250 | 3.5775 | 0.0896 | 0.0447 | 0.0896 | 0.0413 | 0.3453 |
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- | No log | 5.17 | 300 | 3.5078 | 0.0969 | 0.0380 | 0.0969 | 0.0400 | 0.3482 |
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- | No log | 6.03 | 350 | 3.4008 | 0.1283 | 0.0445 | 0.1283 | 0.0587 | 0.3777 |
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- | No log | 6.9 | 400 | 3.3443 | 0.1550 | 0.1089 | 0.1550 | 0.0850 | 0.3983 |
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- | No log | 7.76 | 450 | 3.2965 | 0.1792 | 0.1052 | 0.1792 | 0.1056 | 0.4177 |
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- | 3.768 | 8.62 | 500 | 3.2824 | 0.1864 | 0.1087 | 0.1864 | 0.1114 | 0.4189 |
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- | 3.768 | 9.48 | 550 | 3.2609 | 0.2058 | 0.1339 | 0.2058 | 0.1251 | 0.4332 |
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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: 2.6644
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+ - Accuracy: 0.4576
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+ - Precision: 0.4384
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+ - Recall: 0.4576
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+ - F1: 0.3988
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+ - Binary: 0.6165
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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: 5e-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 | 0.86 | 50 | 4.1527 | 0.0484 | 0.0321 | 0.0484 | 0.0218 | 0.3266 |
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+ | No log | 1.72 | 100 | 3.7623 | 0.0605 | 0.0356 | 0.0605 | 0.0253 | 0.3361 |
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+ | No log | 2.59 | 150 | 3.5557 | 0.1211 | 0.1031 | 0.1211 | 0.0914 | 0.3731 |
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+ | No log | 3.45 | 200 | 3.3630 | 0.2131 | 0.1912 | 0.2131 | 0.1632 | 0.4375 |
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+ | No log | 4.31 | 250 | 3.1590 | 0.2809 | 0.2107 | 0.2809 | 0.2096 | 0.4915 |
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+ | No log | 5.17 | 300 | 3.0569 | 0.3414 | 0.3012 | 0.3414 | 0.2825 | 0.5312 |
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+ | No log | 6.03 | 350 | 2.8798 | 0.3995 | 0.3279 | 0.3995 | 0.3298 | 0.5751 |
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+ | No log | 6.9 | 400 | 2.7761 | 0.4189 | 0.3461 | 0.4189 | 0.3522 | 0.5918 |
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+ | No log | 7.76 | 450 | 2.7086 | 0.4383 | 0.3693 | 0.4383 | 0.3689 | 0.6036 |
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+ | 3.4503 | 8.62 | 500 | 2.6644 | 0.4576 | 0.4384 | 0.4576 | 0.3988 | 0.6165 |
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+ | 3.4503 | 9.48 | 550 | 2.6426 | 0.4649 | 0.4400 | 0.4649 | 0.4021 | 0.6211 |
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  ### Framework versions
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