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sewd_classifier

Audio Classification
Transformers
TensorBoard
Safetensors
sew-d
Generated from Trainer
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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
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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
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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: 2.9680
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- - Accuracy: 0.1648
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- - Precision: 0.1245
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- - Recall: 0.1648
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- - F1: 0.1071
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- - Binary: 0.4086
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  ## Model description
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@@ -55,63 +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 | 0.19 | 50 | 4.4314 | 0.0097 | 0.0024 | 0.0097 | 0.0025 | 0.1521 |
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- | No log | 0.39 | 100 | 4.4174 | 0.0109 | 0.0004 | 0.0109 | 0.0007 | 0.1579 |
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- | No log | 0.58 | 150 | 4.3422 | 0.0146 | 0.0087 | 0.0146 | 0.0051 | 0.1990 |
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- | No log | 0.78 | 200 | 4.2625 | 0.0231 | 0.0070 | 0.0231 | 0.0076 | 0.2200 |
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- | No log | 0.97 | 250 | 4.1728 | 0.0364 | 0.0081 | 0.0364 | 0.0116 | 0.2573 |
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- | 4.3393 | 1.16 | 300 | 4.0986 | 0.0303 | 0.0073 | 0.0303 | 0.0086 | 0.2585 |
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- | 4.3393 | 1.36 | 350 | 4.0162 | 0.0413 | 0.0305 | 0.0413 | 0.0186 | 0.2881 |
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- | 4.3393 | 1.55 | 400 | 3.9676 | 0.0522 | 0.0288 | 0.0522 | 0.0246 | 0.2885 |
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- | 4.3393 | 1.75 | 450 | 3.9007 | 0.0667 | 0.0518 | 0.0667 | 0.0400 | 0.3090 |
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- | 4.3393 | 1.94 | 500 | 3.8441 | 0.0643 | 0.0510 | 0.0643 | 0.0362 | 0.3180 |
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- | 3.9435 | 2.13 | 550 | 3.7809 | 0.0922 | 0.0468 | 0.0922 | 0.0475 | 0.3443 |
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- | 3.9435 | 2.33 | 600 | 3.7491 | 0.0934 | 0.0498 | 0.0934 | 0.0454 | 0.3433 |
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- | 3.9435 | 2.52 | 650 | 3.6902 | 0.0837 | 0.0462 | 0.0837 | 0.0409 | 0.3400 |
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- | 3.9435 | 2.72 | 700 | 3.6293 | 0.0874 | 0.0344 | 0.0874 | 0.0420 | 0.3496 |
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- | 3.9435 | 2.91 | 750 | 3.5813 | 0.0995 | 0.0545 | 0.0995 | 0.0501 | 0.3597 |
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- | 3.6828 | 3.1 | 800 | 3.5425 | 0.1044 | 0.0548 | 0.1044 | 0.0478 | 0.3629 |
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- | 3.6828 | 3.3 | 850 | 3.5029 | 0.1080 | 0.0709 | 0.1080 | 0.0526 | 0.3680 |
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- | 3.6828 | 3.49 | 900 | 3.4698 | 0.1104 | 0.0446 | 0.1104 | 0.0498 | 0.3704 |
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- | 3.6828 | 3.69 | 950 | 3.4183 | 0.1189 | 0.0585 | 0.1189 | 0.0593 | 0.3782 |
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- | 3.6828 | 3.88 | 1000 | 3.3715 | 0.125 | 0.0714 | 0.125 | 0.0631 | 0.3823 |
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- | 3.5039 | 4.07 | 1050 | 3.3397 | 0.1262 | 0.0628 | 0.1262 | 0.0624 | 0.3822 |
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- | 3.5039 | 4.27 | 1100 | 3.3233 | 0.1299 | 0.0714 | 0.1299 | 0.0661 | 0.3842 |
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- | 3.5039 | 4.46 | 1150 | 3.2988 | 0.1238 | 0.0694 | 0.1238 | 0.0643 | 0.3792 |
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- | 3.5039 | 4.66 | 1200 | 3.2719 | 0.1420 | 0.0779 | 0.1420 | 0.0760 | 0.3939 |
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- | 3.5039 | 4.85 | 1250 | 3.2423 | 0.1420 | 0.0686 | 0.1420 | 0.0763 | 0.3950 |
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- | 3.3815 | 5.04 | 1300 | 3.2073 | 0.1432 | 0.0815 | 0.1432 | 0.0788 | 0.3941 |
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- | 3.3815 | 5.24 | 1350 | 3.1905 | 0.1371 | 0.0876 | 0.1371 | 0.0768 | 0.3911 |
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- | 3.3815 | 5.43 | 1400 | 3.1657 | 0.1432 | 0.0767 | 0.1432 | 0.0785 | 0.3959 |
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- | 3.3815 | 5.63 | 1450 | 3.1625 | 0.1456 | 0.0829 | 0.1456 | 0.0833 | 0.3972 |
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- | 3.3815 | 5.82 | 1500 | 3.1418 | 0.1517 | 0.0750 | 0.1517 | 0.0866 | 0.4018 |
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- | 3.2631 | 6.01 | 1550 | 3.1043 | 0.1553 | 0.0769 | 0.1553 | 0.0884 | 0.4030 |
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- | 3.2631 | 6.21 | 1600 | 3.0953 | 0.1614 | 0.0958 | 0.1614 | 0.0989 | 0.4093 |
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- | 3.2631 | 6.4 | 1650 | 3.0787 | 0.1626 | 0.0904 | 0.1626 | 0.0968 | 0.4101 |
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- | 3.2631 | 6.6 | 1700 | 3.0623 | 0.1626 | 0.1054 | 0.1626 | 0.0978 | 0.4092 |
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- | 3.2631 | 6.79 | 1750 | 3.0505 | 0.1602 | 0.0935 | 0.1602 | 0.0943 | 0.4087 |
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- | 3.2631 | 6.98 | 1800 | 3.0358 | 0.1638 | 0.0941 | 0.1638 | 0.0986 | 0.4102 |
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- | 3.1867 | 7.18 | 1850 | 3.0115 | 0.1614 | 0.0836 | 0.1614 | 0.0939 | 0.4092 |
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- | 3.1867 | 7.37 | 1900 | 3.0025 | 0.1711 | 0.1069 | 0.1711 | 0.1056 | 0.4160 |
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- | 3.1867 | 7.57 | 1950 | 3.0081 | 0.1711 | 0.1161 | 0.1711 | 0.1048 | 0.4160 |
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- | 3.1867 | 7.76 | 2000 | 2.9910 | 0.1772 | 0.1077 | 0.1772 | 0.1077 | 0.4198 |
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- | 3.1867 | 7.95 | 2050 | 2.9817 | 0.1760 | 0.1204 | 0.1760 | 0.1091 | 0.4189 |
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- | 3.134 | 8.15 | 2100 | 2.9609 | 0.1833 | 0.1291 | 0.1833 | 0.1155 | 0.4244 |
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- | 3.134 | 8.34 | 2150 | 2.9610 | 0.1772 | 0.1184 | 0.1772 | 0.1090 | 0.4198 |
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- | 3.134 | 8.54 | 2200 | 2.9508 | 0.1808 | 0.1288 | 0.1808 | 0.1123 | 0.4223 |
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- | 3.134 | 8.73 | 2250 | 2.9450 | 0.1845 | 0.1157 | 0.1845 | 0.1139 | 0.4252 |
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- | 3.134 | 8.92 | 2300 | 2.9401 | 0.1845 | 0.1301 | 0.1845 | 0.1171 | 0.4249 |
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- | 3.1045 | 9.12 | 2350 | 2.9368 | 0.1917 | 0.1521 | 0.1917 | 0.1251 | 0.4300 |
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- | 3.1045 | 9.31 | 2400 | 2.9305 | 0.1905 | 0.1388 | 0.1905 | 0.1232 | 0.4291 |
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- | 3.1045 | 9.51 | 2450 | 2.9319 | 0.1893 | 0.1425 | 0.1893 | 0.1218 | 0.4283 |
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- | 3.1045 | 9.7 | 2500 | 2.9288 | 0.1905 | 0.1470 | 0.1905 | 0.1240 | 0.4291 |
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- | 3.1045 | 9.89 | 2550 | 2.9270 | 0.1869 | 0.1374 | 0.1869 | 0.1182 | 0.4266 |
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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
4
  tags:
5
  - generated_from_trainer
 
 
 
 
 
6
  model-index:
7
  - name: sewd_classifier
8
  results: []
 
14
  # sewd_classifier
15
 
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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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  ## 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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