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Nugrahasetyaardi
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SER_model_xapiens_binary

Audio Classification
Transformers
TensorBoard
Safetensors
wav2vec2
Generated from Trainer
Model card Files
xet
Metrics Community
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  1. README.md +102 -5
  2. model.safetensors +1 -1
  3. runs/Jun05_15-04-37_DESKTOP-6VKE8JE/events.out.tfevents.1717574678.DESKTOP-6VKE8JE.23756.10 +2 -2
README.md CHANGED
@@ -17,7 +17,7 @@ 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: 0.6725
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  - Accuracy: 0.6121
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  ## Model description
@@ -46,15 +46,112 @@ The following hyperparameters were used during training:
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_ratio: 0.1
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- - num_epochs: 3
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 1.0 | 9 | 0.6698 | 0.6121 |
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- | 0.6634 | 2.0 | 18 | 0.6709 | 0.6121 |
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- | 0.6571 | 3.0 | 27 | 0.6725 | 0.6121 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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: 1.9238
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  - Accuracy: 0.6121
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  ## Model description
 
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 100
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 9 | 0.6576 | 0.6186 |
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+ | 0.6373 | 2.0 | 18 | 0.6570 | 0.6239 |
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+ | 0.6356 | 3.0 | 27 | 0.6528 | 0.6252 |
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+ | 0.6255 | 4.0 | 36 | 0.6525 | 0.6212 |
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+ | 0.6275 | 5.0 | 45 | 0.6459 | 0.6239 |
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+ | 0.62 | 6.0 | 54 | 0.6564 | 0.6252 |
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+ | 0.6079 | 7.0 | 63 | 0.6575 | 0.6173 |
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+ | 0.6066 | 8.0 | 72 | 0.6592 | 0.6304 |
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+ | 0.6032 | 9.0 | 81 | 0.6540 | 0.6265 |
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+ | 0.5894 | 10.0 | 90 | 0.6553 | 0.6252 |
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+ | 0.5894 | 11.0 | 99 | 0.6764 | 0.6239 |
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+ | 0.5707 | 12.0 | 108 | 0.6768 | 0.6370 |
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+ | 0.5665 | 13.0 | 117 | 0.6877 | 0.6330 |
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+ | 0.5478 | 14.0 | 126 | 0.7169 | 0.6134 |
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+ | 0.5303 | 15.0 | 135 | 0.7437 | 0.5767 |
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+ | 0.5113 | 16.0 | 144 | 0.7235 | 0.6252 |
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+ | 0.4867 | 17.0 | 153 | 0.7914 | 0.6055 |
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+ | 0.4525 | 18.0 | 162 | 0.7906 | 0.6121 |
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+ | 0.4339 | 19.0 | 171 | 0.7946 | 0.6029 |
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+ | 0.4231 | 20.0 | 180 | 0.7982 | 0.6121 |
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+ | 0.4231 | 21.0 | 189 | 0.7991 | 0.6278 |
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+ | 0.3913 | 22.0 | 198 | 0.8757 | 0.6252 |
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+ | 0.3967 | 23.0 | 207 | 0.8746 | 0.6042 |
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+ | 0.3615 | 24.0 | 216 | 0.8731 | 0.5976 |
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+ | 0.3354 | 25.0 | 225 | 0.9350 | 0.6173 |
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+ | 0.3288 | 26.0 | 234 | 0.9604 | 0.6042 |
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+ | 0.3087 | 27.0 | 243 | 0.9534 | 0.6199 |
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+ | 0.2977 | 28.0 | 252 | 0.9491 | 0.6107 |
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+ | 0.2657 | 29.0 | 261 | 1.0096 | 0.6134 |
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+ | 0.2614 | 30.0 | 270 | 1.0069 | 0.6042 |
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+ | 0.2614 | 31.0 | 279 | 1.0388 | 0.5990 |
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+ | 0.2309 | 32.0 | 288 | 1.1028 | 0.5950 |
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+ | 0.2155 | 33.0 | 297 | 1.1211 | 0.6239 |
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+ | 0.2162 | 34.0 | 306 | 1.1376 | 0.5767 |
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+ | 0.2055 | 35.0 | 315 | 1.2133 | 0.5806 |
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+ | 0.1949 | 36.0 | 324 | 1.1371 | 0.5963 |
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+ | 0.1897 | 37.0 | 333 | 1.2791 | 0.5793 |
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+ | 0.1715 | 38.0 | 342 | 1.2176 | 0.5924 |
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+ | 0.1622 | 39.0 | 351 | 1.2985 | 0.5832 |
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+ | 0.1571 | 40.0 | 360 | 1.3201 | 0.5832 |
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+ | 0.1571 | 41.0 | 369 | 1.3364 | 0.5976 |
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+ | 0.1518 | 42.0 | 378 | 1.2600 | 0.6173 |
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+ | 0.1715 | 43.0 | 387 | 1.2334 | 0.6134 |
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+ | 0.1702 | 44.0 | 396 | 1.2732 | 0.6055 |
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+ | 0.1292 | 45.0 | 405 | 1.3833 | 0.5963 |
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+ | 0.1104 | 46.0 | 414 | 1.4520 | 0.5990 |
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+ | 0.1572 | 47.0 | 423 | 1.3802 | 0.6291 |
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+ | 0.132 | 48.0 | 432 | 1.4400 | 0.6003 |
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+ | 0.1528 | 49.0 | 441 | 1.3557 | 0.6212 |
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+ | 0.1219 | 50.0 | 450 | 1.3858 | 0.5911 |
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+ | 0.1219 | 51.0 | 459 | 1.4453 | 0.5937 |
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+ | 0.1014 | 52.0 | 468 | 1.3600 | 0.6212 |
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+ | 0.0951 | 53.0 | 477 | 1.4042 | 0.6186 |
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+ | 0.0962 | 54.0 | 486 | 1.4200 | 0.6199 |
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+ | 0.0937 | 55.0 | 495 | 1.4017 | 0.6291 |
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+ | 0.1005 | 56.0 | 504 | 1.4544 | 0.6081 |
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+ | 0.0832 | 57.0 | 513 | 1.4527 | 0.6252 |
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+ | 0.0896 | 58.0 | 522 | 1.4970 | 0.6068 |
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+ | 0.0754 | 59.0 | 531 | 1.5413 | 0.6016 |
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+ | 0.076 | 60.0 | 540 | 1.5303 | 0.6186 |
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+ | 0.076 | 61.0 | 549 | 1.5076 | 0.6134 |
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+ | 0.0945 | 62.0 | 558 | 1.4725 | 0.6225 |
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+ | 0.0636 | 63.0 | 567 | 1.5103 | 0.6160 |
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+ | 0.0866 | 64.0 | 576 | 1.5384 | 0.6304 |
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+ | 0.0558 | 65.0 | 585 | 1.5868 | 0.6081 |
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+ | 0.0607 | 66.0 | 594 | 1.5560 | 0.6265 |
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+ | 0.0595 | 67.0 | 603 | 1.6161 | 0.6212 |
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+ | 0.0566 | 68.0 | 612 | 1.6855 | 0.5911 |
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+ | 0.042 | 69.0 | 621 | 1.6898 | 0.6186 |
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+ | 0.0506 | 70.0 | 630 | 1.6505 | 0.6330 |
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+ | 0.0506 | 71.0 | 639 | 1.6898 | 0.6107 |
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+ | 0.048 | 72.0 | 648 | 1.6370 | 0.6225 |
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+ | 0.0564 | 73.0 | 657 | 1.6576 | 0.6147 |
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+ | 0.0512 | 74.0 | 666 | 1.7149 | 0.6003 |
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+ | 0.0482 | 75.0 | 675 | 1.7085 | 0.6199 |
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+ | 0.0351 | 76.0 | 684 | 1.7413 | 0.6134 |
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+ | 0.0432 | 77.0 | 693 | 1.7627 | 0.6016 |
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+ | 0.0368 | 78.0 | 702 | 1.7961 | 0.6291 |
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+ | 0.0416 | 79.0 | 711 | 1.7539 | 0.6199 |
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+ | 0.0398 | 80.0 | 720 | 1.7764 | 0.6160 |
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+ | 0.0398 | 81.0 | 729 | 1.8516 | 0.6252 |
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+ | 0.0311 | 82.0 | 738 | 1.8629 | 0.6199 |
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+ | 0.0327 | 83.0 | 747 | 1.8564 | 0.6147 |
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+ | 0.0404 | 84.0 | 756 | 1.8447 | 0.6291 |
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+ | 0.0407 | 85.0 | 765 | 1.8198 | 0.6173 |
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+ | 0.0432 | 86.0 | 774 | 1.8477 | 0.6029 |
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+ | 0.0367 | 87.0 | 783 | 1.8972 | 0.6317 |
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+ | 0.0334 | 88.0 | 792 | 1.8497 | 0.6121 |
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+ | 0.0228 | 89.0 | 801 | 1.8638 | 0.6199 |
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+ | 0.0351 | 90.0 | 810 | 1.8128 | 0.6107 |
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+ | 0.0351 | 91.0 | 819 | 1.8479 | 0.6186 |
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+ | 0.0342 | 92.0 | 828 | 1.8849 | 0.6225 |
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+ | 0.0257 | 93.0 | 837 | 1.9021 | 0.6160 |
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+ | 0.0288 | 94.0 | 846 | 1.9284 | 0.6147 |
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+ | 0.0241 | 95.0 | 855 | 1.9315 | 0.6107 |
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+ | 0.0237 | 96.0 | 864 | 1.9235 | 0.5976 |
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+ | 0.0231 | 97.0 | 873 | 1.9428 | 0.6225 |
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+ | 0.0217 | 98.0 | 882 | 1.9266 | 0.6199 |
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+ | 0.0215 | 99.0 | 891 | 1.9238 | 0.6160 |
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+ | 0.0207 | 100.0 | 900 | 1.9238 | 0.6121 |
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  ### Framework versions
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