wav2vec2-5Class-train-test-finetune-Medium
This model is a fine-tuned version of anderloh/Hugginhface-master-wav2vec-pretreined-5-class-train-test on the anderloh/Master5Class dataset. It achieves the following results on the evaluation set:
- Loss: 0.7855
- Accuracy: 0.7448
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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 0
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 250.0
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
1.6852 | 0.95 | 14 | 1.5987 | 0.3427 |
1.5721 | 1.97 | 29 | 1.5976 | 0.3427 |
1.5696 | 2.98 | 44 | 1.5957 | 0.3427 |
1.5671 | 4.0 | 59 | 1.5932 | 0.3357 |
1.6757 | 4.95 | 73 | 1.5902 | 0.3252 |
1.5595 | 5.97 | 88 | 1.5864 | 0.3217 |
1.5536 | 6.98 | 103 | 1.5818 | 0.3182 |
1.5484 | 8.0 | 118 | 1.5765 | 0.3112 |
1.6506 | 8.95 | 132 | 1.5708 | 0.3077 |
1.5317 | 9.97 | 147 | 1.5641 | 0.3007 |
1.5226 | 10.98 | 162 | 1.5564 | 0.2867 |
1.5116 | 12.0 | 177 | 1.5478 | 0.2692 |
1.6046 | 12.95 | 191 | 1.5385 | 0.2622 |
1.4822 | 13.97 | 206 | 1.5285 | 0.2552 |
1.4614 | 14.98 | 221 | 1.5184 | 0.2552 |
1.4396 | 16.0 | 236 | 1.5101 | 0.2517 |
1.5047 | 16.95 | 250 | 1.5104 | 0.2448 |
1.3741 | 17.97 | 265 | 1.5250 | 0.2517 |
1.3512 | 18.98 | 280 | 1.5329 | 0.2657 |
1.3286 | 20.0 | 295 | 1.5095 | 0.3252 |
1.3967 | 20.95 | 309 | 1.4829 | 0.3497 |
1.2779 | 21.97 | 324 | 1.4598 | 0.3846 |
1.2449 | 22.98 | 339 | 1.4284 | 0.4161 |
1.2118 | 24.0 | 354 | 1.4162 | 0.4231 |
1.2521 | 24.95 | 368 | 1.3798 | 0.4476 |
1.1183 | 25.97 | 383 | 1.3246 | 0.4790 |
1.0778 | 26.98 | 398 | 1.2761 | 0.4930 |
1.0306 | 28.0 | 413 | 1.2300 | 0.5105 |
1.0808 | 28.95 | 427 | 1.2064 | 0.5140 |
0.9767 | 29.97 | 442 | 1.1670 | 0.5524 |
0.9589 | 30.98 | 457 | 1.1264 | 0.5734 |
0.9193 | 32.0 | 472 | 1.1013 | 0.5874 |
0.9462 | 32.95 | 486 | 1.0736 | 0.6049 |
0.85 | 33.97 | 501 | 1.0628 | 0.6049 |
0.8294 | 34.98 | 516 | 1.0473 | 0.6189 |
0.8025 | 36.0 | 531 | 1.0030 | 0.6329 |
0.8206 | 36.95 | 545 | 0.9964 | 0.6399 |
0.7541 | 37.97 | 560 | 0.9605 | 0.6608 |
0.7413 | 38.98 | 575 | 0.9467 | 0.6643 |
0.709 | 40.0 | 590 | 0.9348 | 0.6678 |
0.7817 | 40.95 | 604 | 0.9366 | 0.6678 |
0.7034 | 41.97 | 619 | 0.9109 | 0.6818 |
0.6856 | 42.98 | 634 | 0.9277 | 0.6573 |
0.6625 | 44.0 | 649 | 0.8980 | 0.6783 |
0.7207 | 44.95 | 663 | 0.9050 | 0.6713 |
0.6684 | 45.97 | 678 | 0.8973 | 0.6748 |
0.6651 | 46.98 | 693 | 0.8935 | 0.6783 |
0.6451 | 48.0 | 708 | 0.8945 | 0.6748 |
0.6774 | 48.95 | 722 | 0.8879 | 0.6818 |
0.6308 | 49.97 | 737 | 0.8883 | 0.6818 |
0.6199 | 50.98 | 752 | 0.8826 | 0.6818 |
0.6379 | 52.0 | 767 | 0.8582 | 0.6923 |
0.6588 | 52.95 | 781 | 0.8825 | 0.6818 |
0.5857 | 53.97 | 796 | 0.8808 | 0.6748 |
0.6076 | 54.98 | 811 | 0.8555 | 0.6958 |
0.5934 | 56.0 | 826 | 0.8654 | 0.6888 |
0.6427 | 56.95 | 840 | 0.8616 | 0.6853 |
0.5782 | 57.97 | 855 | 0.8711 | 0.6678 |
0.5819 | 58.98 | 870 | 0.8689 | 0.6748 |
0.5918 | 60.0 | 885 | 0.8602 | 0.6923 |
0.5845 | 60.95 | 899 | 0.8459 | 0.6993 |
0.5667 | 61.97 | 914 | 0.8467 | 0.7028 |
0.5327 | 62.98 | 929 | 0.8540 | 0.6923 |
0.523 | 64.0 | 944 | 0.8323 | 0.7063 |
0.548 | 64.95 | 958 | 0.8407 | 0.6993 |
0.5399 | 65.97 | 973 | 0.8379 | 0.6993 |
0.5324 | 66.98 | 988 | 0.8119 | 0.7028 |
0.5171 | 68.0 | 1003 | 0.8445 | 0.6923 |
0.538 | 68.95 | 1017 | 0.8196 | 0.7098 |
0.5312 | 69.97 | 1032 | 0.8415 | 0.6853 |
0.4914 | 70.98 | 1047 | 0.8184 | 0.6958 |
0.5055 | 72.0 | 1062 | 0.8218 | 0.6923 |
0.5401 | 72.95 | 1076 | 0.8160 | 0.7028 |
0.4966 | 73.97 | 1091 | 0.8238 | 0.6888 |
0.4768 | 74.98 | 1106 | 0.8185 | 0.6993 |
0.4789 | 76.0 | 1121 | 0.8261 | 0.7028 |
0.5176 | 76.95 | 1135 | 0.8110 | 0.7098 |
0.466 | 77.97 | 1150 | 0.8141 | 0.6993 |
0.4736 | 78.98 | 1165 | 0.7970 | 0.7168 |
0.4785 | 80.0 | 1180 | 0.8062 | 0.7098 |
0.5309 | 80.95 | 1194 | 0.8051 | 0.6958 |
0.4571 | 81.97 | 1209 | 0.8024 | 0.7098 |
0.47 | 82.98 | 1224 | 0.8031 | 0.7168 |
0.4525 | 84.0 | 1239 | 0.7911 | 0.7133 |
0.5058 | 84.95 | 1253 | 0.7877 | 0.7133 |
0.4627 | 85.97 | 1268 | 0.7918 | 0.7063 |
0.4343 | 86.98 | 1283 | 0.7882 | 0.7168 |
0.4442 | 88.0 | 1298 | 0.8058 | 0.7133 |
0.4745 | 88.95 | 1312 | 0.7810 | 0.7238 |
0.4282 | 89.97 | 1327 | 0.7951 | 0.7098 |
0.4307 | 90.98 | 1342 | 0.7739 | 0.7168 |
0.4403 | 92.0 | 1357 | 0.7788 | 0.7203 |
0.4567 | 92.95 | 1371 | 0.7927 | 0.7168 |
0.4233 | 93.97 | 1386 | 0.7885 | 0.7203 |
0.4347 | 94.98 | 1401 | 0.7849 | 0.7203 |
0.4167 | 96.0 | 1416 | 0.7880 | 0.7238 |
0.4394 | 96.95 | 1430 | 0.7889 | 0.7203 |
0.4359 | 97.97 | 1445 | 0.7785 | 0.7203 |
0.4085 | 98.98 | 1460 | 0.7852 | 0.7133 |
0.3965 | 100.0 | 1475 | 0.7785 | 0.7273 |
0.445 | 100.95 | 1489 | 0.7826 | 0.7203 |
0.3988 | 101.97 | 1504 | 0.8045 | 0.7098 |
0.4129 | 102.98 | 1519 | 0.7686 | 0.7273 |
0.3937 | 104.0 | 1534 | 0.7912 | 0.7133 |
0.4356 | 104.95 | 1548 | 0.7922 | 0.7133 |
0.3969 | 105.97 | 1563 | 0.7752 | 0.7203 |
0.4051 | 106.98 | 1578 | 0.7917 | 0.7133 |
0.3982 | 108.0 | 1593 | 0.7917 | 0.7098 |
0.4117 | 108.95 | 1607 | 0.8071 | 0.7063 |
0.3666 | 109.97 | 1622 | 0.7840 | 0.7203 |
0.3894 | 110.98 | 1637 | 0.7790 | 0.7238 |
0.3858 | 112.0 | 1652 | 0.7961 | 0.7098 |
0.4037 | 112.95 | 1666 | 0.7822 | 0.7203 |
0.3886 | 113.97 | 1681 | 0.7748 | 0.7238 |
0.3762 | 114.98 | 1696 | 0.7782 | 0.7168 |
0.3444 | 116.0 | 1711 | 0.7746 | 0.7308 |
0.3961 | 116.95 | 1725 | 0.7842 | 0.7203 |
0.3578 | 117.97 | 1740 | 0.7819 | 0.7203 |
0.3578 | 118.98 | 1755 | 0.7806 | 0.7203 |
0.3489 | 120.0 | 1770 | 0.7809 | 0.7238 |
0.3622 | 120.95 | 1784 | 0.7947 | 0.7098 |
0.3545 | 121.97 | 1799 | 0.7878 | 0.7168 |
0.3361 | 122.98 | 1814 | 0.7855 | 0.7168 |
0.3618 | 124.0 | 1829 | 0.7890 | 0.7133 |
0.3472 | 124.95 | 1843 | 0.7810 | 0.7168 |
0.3511 | 125.97 | 1858 | 0.7897 | 0.7133 |
0.3389 | 126.98 | 1873 | 0.7923 | 0.7133 |
0.3391 | 128.0 | 1888 | 0.7782 | 0.7273 |
0.3746 | 128.95 | 1902 | 0.7838 | 0.7203 |
0.3238 | 129.97 | 1917 | 0.7943 | 0.7168 |
0.3601 | 130.98 | 1932 | 0.7863 | 0.7168 |
0.3339 | 132.0 | 1947 | 0.7949 | 0.7133 |
0.3805 | 132.95 | 1961 | 0.7823 | 0.7238 |
0.3524 | 133.97 | 1976 | 0.8052 | 0.7098 |
0.3103 | 134.98 | 1991 | 0.7809 | 0.7238 |
0.3484 | 136.0 | 2006 | 0.7879 | 0.7203 |
0.3424 | 136.95 | 2020 | 0.7875 | 0.7273 |
0.316 | 137.97 | 2035 | 0.7829 | 0.7273 |
0.3171 | 138.98 | 2050 | 0.7882 | 0.7203 |
0.3155 | 140.0 | 2065 | 0.7830 | 0.7168 |
0.3382 | 140.95 | 2079 | 0.7826 | 0.7273 |
0.3175 | 141.97 | 2094 | 0.7964 | 0.7203 |
0.3444 | 142.98 | 2109 | 0.7859 | 0.7238 |
0.3208 | 144.0 | 2124 | 0.7860 | 0.7273 |
0.3286 | 144.95 | 2138 | 0.7869 | 0.7273 |
0.3319 | 145.97 | 2153 | 0.7916 | 0.7168 |
0.2954 | 146.98 | 2168 | 0.7938 | 0.7238 |
0.3283 | 148.0 | 2183 | 0.7974 | 0.7168 |
0.3306 | 148.95 | 2197 | 0.7795 | 0.7308 |
0.3073 | 149.97 | 2212 | 0.7910 | 0.7203 |
0.3089 | 150.98 | 2227 | 0.7942 | 0.7203 |
0.2915 | 152.0 | 2242 | 0.7934 | 0.7168 |
0.3286 | 152.95 | 2256 | 0.7808 | 0.7308 |
0.2817 | 153.97 | 2271 | 0.7788 | 0.7308 |
0.3118 | 154.98 | 2286 | 0.7898 | 0.7273 |
0.3155 | 156.0 | 2301 | 0.7966 | 0.7203 |
0.3156 | 156.95 | 2315 | 0.7947 | 0.7203 |
0.2936 | 157.97 | 2330 | 0.7917 | 0.7168 |
0.3049 | 158.98 | 2345 | 0.7780 | 0.7308 |
0.2896 | 160.0 | 2360 | 0.7926 | 0.7273 |
0.3194 | 160.95 | 2374 | 0.8023 | 0.7203 |
0.2918 | 161.97 | 2389 | 0.7933 | 0.7273 |
0.2992 | 162.98 | 2404 | 0.7829 | 0.7413 |
0.3 | 164.0 | 2419 | 0.7946 | 0.7203 |
0.322 | 164.95 | 2433 | 0.7969 | 0.7273 |
0.2994 | 165.97 | 2448 | 0.8076 | 0.7238 |
0.2849 | 166.98 | 2463 | 0.7951 | 0.7308 |
0.2745 | 168.0 | 2478 | 0.7892 | 0.7343 |
0.2974 | 168.95 | 2492 | 0.7916 | 0.7308 |
0.2656 | 169.97 | 2507 | 0.7995 | 0.7343 |
0.295 | 170.98 | 2522 | 0.8026 | 0.7238 |
0.2791 | 172.0 | 2537 | 0.7973 | 0.7343 |
0.2836 | 172.95 | 2551 | 0.8023 | 0.7308 |
0.2806 | 173.97 | 2566 | 0.8013 | 0.7308 |
0.2661 | 174.98 | 2581 | 0.7965 | 0.7308 |
0.2695 | 176.0 | 2596 | 0.8063 | 0.7273 |
0.286 | 176.95 | 2610 | 0.7963 | 0.7238 |
0.2743 | 177.97 | 2625 | 0.7929 | 0.7413 |
0.2775 | 178.98 | 2640 | 0.7855 | 0.7448 |
0.2878 | 180.0 | 2655 | 0.7894 | 0.7378 |
0.2757 | 180.95 | 2669 | 0.8013 | 0.7273 |
0.3067 | 181.97 | 2684 | 0.8015 | 0.7308 |
0.2412 | 182.98 | 2699 | 0.7975 | 0.7273 |
0.2686 | 184.0 | 2714 | 0.8037 | 0.7238 |
0.3176 | 184.95 | 2728 | 0.8017 | 0.7308 |
0.269 | 185.97 | 2743 | 0.8060 | 0.7308 |
0.2668 | 186.98 | 2758 | 0.8030 | 0.7308 |
0.2761 | 188.0 | 2773 | 0.8007 | 0.7413 |
0.2731 | 188.95 | 2787 | 0.8039 | 0.7343 |
0.2678 | 189.97 | 2802 | 0.8054 | 0.7308 |
0.2686 | 190.98 | 2817 | 0.8042 | 0.7343 |
0.2721 | 192.0 | 2832 | 0.8063 | 0.7308 |
0.3111 | 192.95 | 2846 | 0.8075 | 0.7378 |
0.2525 | 193.97 | 2861 | 0.8114 | 0.7273 |
0.2589 | 194.98 | 2876 | 0.8071 | 0.7413 |
0.2597 | 196.0 | 2891 | 0.8161 | 0.7378 |
0.3034 | 196.95 | 2905 | 0.8163 | 0.7378 |
0.2721 | 197.97 | 2920 | 0.8151 | 0.7308 |
0.2783 | 198.98 | 2935 | 0.8093 | 0.7448 |
0.259 | 200.0 | 2950 | 0.8026 | 0.7413 |
0.2896 | 200.95 | 2964 | 0.8070 | 0.7308 |
0.2584 | 201.97 | 2979 | 0.8113 | 0.7308 |
0.2672 | 202.98 | 2994 | 0.8096 | 0.7343 |
0.2622 | 204.0 | 3009 | 0.8060 | 0.7413 |
0.2677 | 204.95 | 3023 | 0.8084 | 0.7343 |
0.263 | 205.97 | 3038 | 0.8010 | 0.7378 |
0.2608 | 206.98 | 3053 | 0.7989 | 0.7448 |
0.2528 | 208.0 | 3068 | 0.7954 | 0.7448 |
0.2553 | 208.95 | 3082 | 0.7965 | 0.7413 |
0.2652 | 209.97 | 3097 | 0.7995 | 0.7413 |
0.246 | 210.98 | 3112 | 0.8026 | 0.7378 |
0.2665 | 212.0 | 3127 | 0.8049 | 0.7378 |
0.2731 | 212.95 | 3141 | 0.8052 | 0.7378 |
0.2539 | 213.97 | 3156 | 0.8089 | 0.7378 |
0.2376 | 214.98 | 3171 | 0.8116 | 0.7378 |
0.2667 | 216.0 | 3186 | 0.8099 | 0.7413 |
0.2768 | 216.95 | 3200 | 0.8079 | 0.7413 |
0.2551 | 217.97 | 3215 | 0.8065 | 0.7448 |
0.256 | 218.98 | 3230 | 0.8080 | 0.7413 |
0.2387 | 220.0 | 3245 | 0.8076 | 0.7448 |
0.2736 | 220.95 | 3259 | 0.8081 | 0.7448 |
0.2551 | 221.97 | 3274 | 0.8092 | 0.7448 |
0.2482 | 222.98 | 3289 | 0.8085 | 0.7448 |
0.2432 | 224.0 | 3304 | 0.8085 | 0.7448 |
0.2857 | 224.95 | 3318 | 0.8079 | 0.7448 |
0.2434 | 225.97 | 3333 | 0.8079 | 0.7448 |
0.2531 | 226.98 | 3348 | 0.8078 | 0.7448 |
0.222 | 228.0 | 3363 | 0.8093 | 0.7448 |
0.2651 | 228.95 | 3377 | 0.8105 | 0.7448 |
0.2886 | 229.97 | 3392 | 0.8116 | 0.7448 |
0.2534 | 230.98 | 3407 | 0.8116 | 0.7448 |
0.2483 | 232.0 | 3422 | 0.8116 | 0.7448 |
0.272 | 232.95 | 3436 | 0.8118 | 0.7448 |
0.2562 | 233.97 | 3451 | 0.8120 | 0.7448 |
0.2531 | 234.98 | 3466 | 0.8122 | 0.7448 |
0.2397 | 236.0 | 3481 | 0.8123 | 0.7448 |
0.2573 | 236.95 | 3495 | 0.8123 | 0.7448 |
0.2023 | 237.29 | 3500 | 0.8122 | 0.7448 |
Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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