generated_from_trainer

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xlsr-syntesized-turkish-8-hour-llr-2

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on an unknown dataset. It achieves the following results on the evaluation set:

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:

Training results

Training Loss Epoch Step Validation Loss Wer
3.8595 0.26 100 3.0079 1.0
2.6103 0.52 200 1.6661 1.0
1.0733 0.78 300 0.8518 0.9716
0.7436 1.04 400 0.4824 0.6979
0.5821 1.3 500 0.4184 0.6479
0.5916 1.56 600 0.4041 0.6042
0.5099 1.82 700 0.3637 0.6122
0.4787 2.08 800 0.3393 0.5328
0.4304 2.34 900 0.3145 0.4870
0.4366 2.6 1000 0.3054 0.4718
0.4144 2.86 1100 0.3118 0.4915
0.4303 3.12 1200 0.3303 0.4612
0.3768 3.39 1300 0.3169 0.4844
0.39 3.65 1400 0.2931 0.4351
0.3717 3.91 1500 0.2824 0.4303
0.3396 4.17 1600 0.2606 0.3929
0.341 4.43 1700 0.2845 0.4712
0.3427 4.69 1800 0.2820 0.4452
0.3285 4.95 1900 0.2577 0.3957
0.3011 5.21 2000 0.2486 0.3717
0.2923 5.47 2100 0.2482 0.3990
0.298 5.73 2200 0.2333 0.3858
0.2939 5.99 2300 0.2435 0.3900
0.285 6.25 2400 0.2884 0.4040
0.2763 6.51 2500 0.2518 0.3880
0.2764 6.77 2600 0.2429 0.3832
0.2711 7.03 2700 0.2408 0.3729
0.2457 7.29 2800 0.2270 0.3799
0.2428 7.55 2900 0.2354 0.3761
0.2457 7.81 3000 0.2309 0.3640
0.2413 8.07 3100 0.2408 0.3426
0.224 8.33 3200 0.2233 0.3452
0.2295 8.59 3300 0.2324 0.3320
0.2316 8.85 3400 0.2329 0.3434
0.2156 9.11 3500 0.2506 0.3493
0.2057 9.38 3600 0.2416 0.3475
0.2091 9.64 3700 0.2421 0.3413
0.2105 9.9 3800 0.2557 0.3514
0.2086 10.16 3900 0.2281 0.3365
0.1848 10.42 4000 0.2267 0.3214
0.203 10.68 4100 0.2292 0.3598
0.1863 10.94 4200 0.2242 0.3527
0.1732 11.2 4300 0.2426 0.3359
0.1774 11.46 4400 0.2313 0.3438
0.1699 11.72 4500 0.2326 0.3343
0.171 11.98 4600 0.2360 0.3124
0.1691 12.24 4700 0.2566 0.3322
0.1632 12.5 4800 0.2556 0.2985
0.1637 12.76 4900 0.2536 0.3161
0.1619 13.02 5000 0.2418 0.3493
0.1476 13.28 5100 0.2419 0.3159
0.1542 13.54 5200 0.2742 0.3214
0.1481 13.8 5300 0.2454 0.2971
0.1446 14.06 5400 0.2520 0.2910
0.137 14.32 5500 0.2470 0.2980
0.1365 14.58 5600 0.2563 0.3008
0.1369 14.84 5700 0.2620 0.3033
0.1285 15.1 5800 0.2735 0.2861
0.1266 15.36 5900 0.2816 0.2948
0.1285 15.62 6000 0.2842 0.2890
0.1281 15.89 6100 0.2715 0.2889
0.1264 16.15 6200 0.2779 0.2954
0.1178 16.41 6300 0.2944 0.3113
0.1252 16.67 6400 0.2837 0.2901
0.119 16.93 6500 0.2861 0.3111
0.1203 17.19 6600 0.2785 0.3054
0.1108 17.45 6700 0.2823 0.3101
0.11 17.71 6800 0.2871 0.2926
0.11 17.97 6900 0.2803 0.2995
0.1065 18.23 7000 0.2920 0.2947
0.1047 18.49 7100 0.3047 0.2972
0.1123 18.75 7200 0.2945 0.2978
0.1159 19.01 7300 0.2999 0.2976
0.1061 19.27 7400 0.2954 0.2945
0.1011 19.53 7500 0.3024 0.2969
0.1007 19.79 7600 0.3058 0.2940

Framework versions