whisper_tn_hi
This model is a fine-tuned version of openai/whisper-tiny on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.6400
- Wer: 147.3885
- Cer: 295.3741
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 100
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
---|---|---|---|---|---|
1.6414 | 1.0 | 409 | 0.8809 | 83.9795 | 248.4138 |
0.531 | 2.0 | 818 | 0.6346 | 75.4042 | 280.7284 |
0.3538 | 3.0 | 1227 | 0.5810 | 69.8595 | 259.1276 |
0.2679 | 4.0 | 1636 | 0.5639 | 84.1488 | 332.292 |
0.2074 | 5.0 | 2045 | 0.5715 | 85.9773 | 264.435 |
0.1599 | 6.0 | 2454 | 0.6074 | 86.481 | 262.8894 |
0.1216 | 7.0 | 2863 | 0.6402 | 110.0398 | 285.4649 |
0.0903 | 8.0 | 3272 | 0.6736 | 92.7961 | 278.7952 |
0.0663 | 9.0 | 3681 | 0.7023 | 96.3896 | 268.8475 |
0.0472 | 10.0 | 4090 | 0.7527 | 104.0041 | 276.3805 |
0.0335 | 11.0 | 4499 | 0.7907 | 99.0646 | 274.9479 |
0.0235 | 12.0 | 4908 | 0.8320 | 128.1004 | 282.2682 |
0.0169 | 13.0 | 5317 | 0.8741 | 116.1305 | 277.659 |
0.0124 | 14.0 | 5726 | 0.9090 | 137.6534 | 290.6719 |
0.0094 | 15.0 | 6135 | 0.9492 | 117.0405 | 285.2422 |
0.007 | 16.0 | 6544 | 0.9905 | 122.1663 | 280.3801 |
0.0061 | 17.0 | 6953 | 1.0199 | 125.0656 | 277.5049 |
0.0051 | 18.0 | 7362 | 1.0383 | 117.3368 | 278.8806 |
0.0044 | 19.0 | 7771 | 1.0617 | 110.8736 | 275.7667 |
0.0041 | 20.0 | 8180 | 1.0867 | 142.9061 | 291.1584 |
0.0037 | 21.0 | 8589 | 1.1224 | 119.377 | 273.63 |
0.0026 | 22.0 | 8998 | 1.1322 | 158.2452 | 295.0852 |
0.0024 | 23.0 | 9407 | 1.1619 | 134.9446 | 283.1038 |
0.0022 | 24.0 | 9816 | 1.1677 | 124.5789 | 283.5701 |
0.002 | 25.0 | 10225 | 1.1898 | 125.0275 | 288.5318 |
0.0019 | 26.0 | 10634 | 1.1994 | 138.0386 | 288.9011 |
0.0023 | 27.0 | 11043 | 1.2216 | 119.7071 | 279.7329 |
0.0021 | 28.0 | 11452 | 1.2521 | 96.3388 | 266.6656 |
0.0018 | 29.0 | 11861 | 1.2568 | 148.4932 | 288.7504 |
0.0018 | 30.0 | 12270 | 1.2541 | 115.3771 | 283.8205 |
0.0021 | 31.0 | 12679 | 1.2291 | 98.8995 | 271.6817 |
0.0014 | 32.0 | 13088 | 1.2821 | 130.6654 | 293.2197 |
0.0014 | 33.0 | 13497 | 1.2804 | 121.8954 | 287.2249 |
0.0013 | 34.0 | 13906 | 1.2802 | 137.5857 | 293.6275 |
0.0015 | 35.0 | 14315 | 1.3010 | 147.5789 | 296.7907 |
0.0014 | 36.0 | 14724 | 1.2945 | 139.6766 | 292.4335 |
0.0012 | 37.0 | 15133 | 1.3310 | 144.5653 | 288.2045 |
0.0011 | 38.0 | 15542 | 1.3200 | 160.6493 | 306.8297 |
0.0009 | 39.0 | 15951 | 1.3394 | 211.9783 | 341.8621 |
0.0013 | 40.0 | 16360 | 1.3367 | 133.4166 | 304.8621 |
0.0007 | 41.0 | 16769 | 1.3472 | 154.6601 | 319.8702 |
0.0005 | 42.0 | 17178 | 1.3617 | 149.0815 | 301.4669 |
0.0009 | 43.0 | 17587 | 1.3570 | 163.2312 | 319.4675 |
0.0009 | 44.0 | 17996 | 1.3723 | 149.9915 | 310.0088 |
0.0009 | 45.0 | 18405 | 1.3809 | 133.1118 | 289.5232 |
0.0009 | 46.0 | 18814 | 1.3664 | 166.6427 | 308.9287 |
0.0008 | 47.0 | 19223 | 1.3894 | 150.0127 | 304.3739 |
0.0005 | 48.0 | 19632 | 1.3632 | 129.4929 | 307.7766 |
0.0005 | 49.0 | 20041 | 1.3917 | 143.9304 | 313.3529 |
0.0005 | 50.0 | 20450 | 1.4006 | 113.0111 | 295.1966 |
0.0007 | 51.0 | 20859 | 1.3966 | 158.3129 | 303.4328 |
0.0009 | 52.0 | 21268 | 1.4149 | 138.1613 | 304.2098 |
0.0003 | 53.0 | 21677 | 1.3998 | 163.519 | 314.8466 |
0.0002 | 54.0 | 22086 | 1.4192 | 141.4035 | 302.2313 |
0.0001 | 55.0 | 22495 | 1.4183 | 150.2878 | 300.9336 |
0.0002 | 56.0 | 22904 | 1.4281 | 172.598 | 321.0298 |
0.0018 | 57.0 | 23313 | 1.4229 | 151.9597 | 309.6211 |
0.0009 | 58.0 | 23722 | 1.4263 | 128.9554 | 290.2265 |
0.0003 | 59.0 | 24131 | 1.4430 | 135.6599 | 301.7223 |
0.0002 | 60.0 | 24540 | 1.4487 | 156.1034 | 307.6167 |
0.0004 | 61.0 | 24949 | 1.4252 | 107.7161 | 272.8312 |
0.0001 | 62.0 | 25358 | 1.4254 | 123.5122 | 289.272 |
0.0 | 63.0 | 25767 | 1.4510 | 121.2901 | 280.6162 |
0.0002 | 64.0 | 26176 | 1.4407 | 111.6482 | 284.5364 |
0.0003 | 65.0 | 26585 | 1.4512 | 123.5207 | 285.948 |
0.0006 | 66.0 | 26994 | 1.4476 | 108.9224 | 280.1608 |
0.0005 | 67.0 | 27403 | 1.4721 | 153.8178 | 309.4788 |
0.0004 | 68.0 | 27812 | 1.4675 | 132.1341 | 289.9678 |
0.0001 | 69.0 | 28221 | 1.4712 | 135.9096 | 292.8338 |
0.0001 | 70.0 | 28630 | 1.4712 | 137.0228 | 294.8725 |
0.0 | 71.0 | 29039 | 1.4727 | 137.9582 | 292.8438 |
0.0 | 72.0 | 29448 | 1.4766 | 135.6514 | 291.9329 |
0.0 | 73.0 | 29857 | 1.4808 | 135.7784 | 292.3431 |
0.0 | 74.0 | 30266 | 1.4850 | 135.5414 | 291.5527 |
0.0 | 75.0 | 30675 | 1.4901 | 134.3224 | 290.6803 |
0.0 | 76.0 | 31084 | 1.4943 | 135.9562 | 291.6507 |
0.0 | 77.0 | 31493 | 1.4986 | 136.0069 | 291.0294 |
0.0 | 78.0 | 31902 | 1.5039 | 139.228 | 292.1162 |
0.0 | 79.0 | 32311 | 1.5092 | 138.6862 | 291.7796 |
0.0 | 80.0 | 32720 | 1.5146 | 139.8375 | 292.3959 |
0.0 | 81.0 | 33129 | 1.5208 | 138.9782 | 292.097 |
0.0 | 82.0 | 33538 | 1.5270 | 140.976 | 293.3127 |
0.0 | 83.0 | 33947 | 1.5334 | 141.3993 | 292.2359 |
0.0 | 84.0 | 34356 | 1.5401 | 141.2258 | 292.2309 |
0.0 | 85.0 | 34765 | 1.5472 | 140.7686 | 291.4648 |
0.0 | 86.0 | 35174 | 1.5550 | 140.6163 | 291.7997 |
0.0 | 87.0 | 35583 | 1.5617 | 142.9104 | 293.0816 |
0.0 | 88.0 | 35992 | 1.5700 | 140.9972 | 292.0618 |
0.0 | 89.0 | 36401 | 1.5781 | 141.5559 | 292.3054 |
0.0 | 90.0 | 36810 | 1.5855 | 142.4109 | 293.033 |
0.0 | 91.0 | 37219 | 1.5925 | 145.0436 | 293.8586 |
0.0 | 92.0 | 37628 | 1.6010 | 144.2648 | 293.2315 |
0.0 | 93.0 | 38037 | 1.6083 | 144.3833 | 293.3211 |
0.0 | 94.0 | 38446 | 1.6153 | 146.3007 | 294.4095 |
0.0 | 95.0 | 38855 | 1.6207 | 146.9864 | 295.1798 |
0.0 | 96.0 | 39264 | 1.6269 | 145.179 | 293.7054 |
0.0 | 97.0 | 39673 | 1.6321 | 148.0107 | 295.6043 |
0.0 | 98.0 | 40082 | 1.6358 | 147.088 | 295.2686 |
0.0 | 99.0 | 40491 | 1.6389 | 148.1503 | 295.822 |
0.0 | 100.0 | 40900 | 1.6400 | 147.3885 | 295.3741 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.13.0
- Datasets 2.6.1
- Tokenizers 0.11.0
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