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sewd-classifier-aug

Audio Classification
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TensorBoard
Safetensors
sew-d
Generated from Trainer
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 Metrics Community
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README.md CHANGED
@@ -3,11 +3,6 @@ license: apache-2.0
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  base_model: asapp/sew-d-tiny-100k-ft-ls100h
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  tags:
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  - generated_from_trainer
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- metrics:
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- - accuracy
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- - precision
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- - recall
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- - f1
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  model-index:
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  - name: sewd-classifier-aug
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  results: []
@@ -19,13 +14,6 @@ should probably proofread and complete it, then remove this comment. -->
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  # sewd-classifier-aug
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  This model is a fine-tuned version of [asapp/sew-d-tiny-100k-ft-ls100h](https://huggingface.co/asapp/sew-d-tiny-100k-ft-ls100h) on an unknown dataset.
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- It achieves the following results on the evaluation set:
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- - Loss: 1.4895
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- - Accuracy: 0.5850
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- - Precision: 0.5994
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- - Recall: 0.5850
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- - F1: 0.5568
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- - Binary: 0.7090
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  ## Model description
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@@ -55,56 +43,6 @@ The following hyperparameters were used during training:
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  - num_epochs: 10
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  - mixed_precision_training: Native AMP
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- ### Training results
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-
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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 | 0.17 | 50 | 4.4263 | 0.0170 | 0.0011 | 0.0170 | 0.0020 | 0.1544 |
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- | No log | 0.35 | 100 | 4.1870 | 0.0510 | 0.0052 | 0.0510 | 0.0092 | 0.3197 |
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- | No log | 0.52 | 150 | 3.9314 | 0.0655 | 0.0131 | 0.0655 | 0.0184 | 0.3323 |
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- | No log | 0.69 | 200 | 3.6718 | 0.0752 | 0.0182 | 0.0752 | 0.0253 | 0.3439 |
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- | No log | 0.86 | 250 | 3.5228 | 0.0752 | 0.0125 | 0.0752 | 0.0195 | 0.3454 |
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- | 4.0124 | 1.04 | 300 | 3.3917 | 0.0947 | 0.0297 | 0.0947 | 0.0388 | 0.3575 |
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- | 4.0124 | 1.21 | 350 | 3.2951 | 0.1019 | 0.0379 | 0.1019 | 0.0392 | 0.3663 |
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- | 4.0124 | 1.38 | 400 | 3.2286 | 0.0850 | 0.0436 | 0.0850 | 0.0368 | 0.3544 |
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- | 4.0124 | 1.55 | 450 | 3.1450 | 0.1044 | 0.0406 | 0.1044 | 0.0409 | 0.3687 |
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- | 4.0124 | 1.73 | 500 | 3.0633 | 0.1238 | 0.0676 | 0.1238 | 0.0604 | 0.3830 |
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- | 4.0124 | 1.9 | 550 | 3.0132 | 0.1650 | 0.0991 | 0.1650 | 0.0932 | 0.4090 |
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- | 3.3037 | 2.07 | 600 | 2.9268 | 0.1917 | 0.1021 | 0.1917 | 0.1095 | 0.4323 |
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- | 3.3037 | 2.24 | 650 | 2.8325 | 0.2330 | 0.1891 | 0.2330 | 0.1601 | 0.4609 |
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- | 3.3037 | 2.42 | 700 | 2.7457 | 0.2403 | 0.1651 | 0.2403 | 0.1497 | 0.4638 |
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- | 3.3037 | 2.59 | 750 | 2.6771 | 0.2379 | 0.1440 | 0.2379 | 0.1490 | 0.4660 |
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- | 3.3037 | 2.76 | 800 | 2.5887 | 0.2621 | 0.2409 | 0.2621 | 0.1943 | 0.4813 |
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- | 3.3037 | 2.93 | 850 | 2.5040 | 0.3277 | 0.2904 | 0.3277 | 0.2537 | 0.5272 |
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- | 2.9498 | 3.11 | 900 | 2.4614 | 0.3325 | 0.2893 | 0.3325 | 0.2632 | 0.5306 |
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- | 2.9498 | 3.28 | 950 | 2.3817 | 0.3519 | 0.3013 | 0.3519 | 0.2803 | 0.5459 |
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- | 2.9498 | 3.45 | 1000 | 2.3218 | 0.3859 | 0.3999 | 0.3859 | 0.3388 | 0.5680 |
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- | 2.9498 | 3.62 | 1050 | 2.2708 | 0.3835 | 0.3416 | 0.3835 | 0.3197 | 0.5648 |
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- | 2.9498 | 3.8 | 1100 | 2.2084 | 0.4102 | 0.3937 | 0.4102 | 0.3464 | 0.5867 |
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- | 2.9498 | 3.97 | 1150 | 2.1359 | 0.4369 | 0.4005 | 0.4369 | 0.3755 | 0.6049 |
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- | 2.6444 | 4.14 | 1200 | 2.0892 | 0.4150 | 0.3960 | 0.4150 | 0.3512 | 0.5883 |
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- | 2.6444 | 4.31 | 1250 | 2.0477 | 0.4539 | 0.4336 | 0.4539 | 0.3994 | 0.6165 |
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- | 2.6444 | 4.49 | 1300 | 1.9899 | 0.4636 | 0.4418 | 0.4636 | 0.4068 | 0.6240 |
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- | 2.6444 | 4.66 | 1350 | 1.9278 | 0.4903 | 0.4689 | 0.4903 | 0.4273 | 0.6427 |
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- | 2.6444 | 4.83 | 1400 | 1.8890 | 0.5024 | 0.5021 | 0.5024 | 0.4506 | 0.6498 |
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- | 2.416 | 5.0 | 1450 | 1.8641 | 0.5049 | 0.5317 | 0.5049 | 0.4620 | 0.6546 |
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- | 2.416 | 5.18 | 1500 | 1.8336 | 0.5073 | 0.4961 | 0.5073 | 0.4619 | 0.6546 |
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- | 2.416 | 5.35 | 1550 | 1.7942 | 0.5146 | 0.4953 | 0.5146 | 0.4657 | 0.6580 |
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- | 2.416 | 5.52 | 1600 | 1.7594 | 0.5194 | 0.5033 | 0.5194 | 0.4759 | 0.6633 |
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- | 2.416 | 5.69 | 1650 | 1.7332 | 0.5437 | 0.5138 | 0.5437 | 0.4898 | 0.6801 |
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- | 2.416 | 5.87 | 1700 | 1.6677 | 0.5631 | 0.5754 | 0.5631 | 0.5286 | 0.6937 |
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- | 2.2366 | 6.04 | 1750 | 1.6683 | 0.5461 | 0.5261 | 0.5461 | 0.5080 | 0.6811 |
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- | 2.2366 | 6.21 | 1800 | 1.6448 | 0.5631 | 0.5685 | 0.5631 | 0.5239 | 0.6930 |
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- | 2.2366 | 6.38 | 1850 | 1.6221 | 0.5801 | 0.5925 | 0.5801 | 0.5425 | 0.7046 |
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- | 2.2366 | 6.56 | 1900 | 1.5782 | 0.5874 | 0.5895 | 0.5874 | 0.5566 | 0.7097 |
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- | 2.2366 | 6.73 | 1950 | 1.5599 | 0.5971 | 0.6129 | 0.5971 | 0.5646 | 0.7167 |
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- | 2.2366 | 6.9 | 2000 | 1.5466 | 0.5971 | 0.6071 | 0.5971 | 0.5632 | 0.7184 |
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- | 2.1169 | 7.08 | 2050 | 1.5010 | 0.5971 | 0.6173 | 0.5971 | 0.5725 | 0.7182 |
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- | 2.1169 | 7.25 | 2100 | 1.4868 | 0.5898 | 0.6164 | 0.5898 | 0.5659 | 0.7114 |
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- | 2.1169 | 7.42 | 2150 | 1.4920 | 0.5850 | 0.5913 | 0.5850 | 0.5582 | 0.7107 |
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- | 2.1169 | 7.59 | 2200 | 1.4895 | 0.5850 | 0.5994 | 0.5850 | 0.5568 | 0.7090 |
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-
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-
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  ### Framework versions
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  - Transformers 4.38.2
 
3
  base_model: asapp/sew-d-tiny-100k-ft-ls100h
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  tags:
5
  - generated_from_trainer
 
 
 
 
 
6
  model-index:
7
  - name: sewd-classifier-aug
8
  results: []
 
14
  # sewd-classifier-aug
15
 
16
  This model is a fine-tuned version of [asapp/sew-d-tiny-100k-ft-ls100h](https://huggingface.co/asapp/sew-d-tiny-100k-ft-ls100h) on an unknown dataset.
 
 
 
 
 
 
 
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  ## Model description
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  - num_epochs: 10
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  - mixed_precision_training: Native AMP
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  ### Framework versions
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  - Transformers 4.38.2
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