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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: wav2vec2-common_voice13
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_13_0
type: common_voice_13_0
config: tr
split: test
args: tr
metrics:
- name: Wer
type: wer
value: 0.2934764687562973
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-common_voice13
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3366
- Wer: 0.2935
## 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: 0.0003
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 20.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 4.0301 | 0.08 | 100 | 4.0286 | 1.0 |
| 3.1668 | 0.15 | 200 | 3.2323 | 1.0 |
| 2.3413 | 0.23 | 300 | 2.1300 | 0.9986 |
| 1.4546 | 0.31 | 400 | 0.8731 | 0.7629 |
| 1.4595 | 0.38 | 500 | 0.7366 | 0.7386 |
| 1.1903 | 0.46 | 600 | 0.6131 | 0.6645 |
| 1.1586 | 0.53 | 700 | 0.5491 | 0.6195 |
| 0.8275 | 0.61 | 800 | 0.5159 | 0.5923 |
| 1.0042 | 0.69 | 900 | 0.5153 | 0.6040 |
| 0.9428 | 0.76 | 1000 | 0.4629 | 0.5602 |
| 0.7592 | 0.84 | 1100 | 0.4670 | 0.5520 |
| 0.8284 | 0.92 | 1200 | 0.4455 | 0.5760 |
| 0.7736 | 0.99 | 1300 | 0.4571 | 0.5480 |
| 0.4047 | 1.07 | 1400 | 0.3962 | 0.4940 |
| 0.3543 | 1.14 | 1500 | 0.4018 | 0.4969 |
| 0.3898 | 1.22 | 1600 | 0.3901 | 0.4862 |
| 0.3827 | 1.3 | 1700 | 0.3982 | 0.4954 |
| 0.3316 | 1.37 | 1800 | 0.4139 | 0.5032 |
| 0.3365 | 1.45 | 1900 | 0.3964 | 0.4878 |
| 0.251 | 1.53 | 2000 | 0.4028 | 0.4899 |
| 0.2419 | 1.6 | 2100 | 0.3991 | 0.5190 |
| 0.3094 | 1.68 | 2200 | 0.3700 | 0.4865 |
| 0.3459 | 1.75 | 2300 | 0.3652 | 0.4850 |
| 0.3085 | 1.83 | 2400 | 0.3806 | 0.4742 |
| 0.4463 | 1.91 | 2500 | 0.3804 | 0.4729 |
| 0.2359 | 1.98 | 2600 | 0.3696 | 0.4635 |
| 0.1502 | 2.06 | 2700 | 0.3764 | 0.4602 |
| 0.2819 | 2.14 | 2800 | 0.3740 | 0.4499 |
| 0.22 | 2.21 | 2900 | 0.3811 | 0.4597 |
| 0.287 | 2.29 | 3000 | 0.3562 | 0.4334 |
| 0.2531 | 2.36 | 3100 | 0.3700 | 0.4442 |
| 0.3143 | 2.44 | 3200 | 0.3548 | 0.4333 |
| 0.203 | 2.52 | 3300 | 0.3659 | 0.4558 |
| 0.2609 | 2.59 | 3400 | 0.3557 | 0.4468 |
| 0.191 | 2.67 | 3500 | 0.3476 | 0.4281 |
| 0.1354 | 2.75 | 3600 | 0.3650 | 0.4354 |
| 0.2345 | 2.82 | 3700 | 0.3479 | 0.4385 |
| 0.1951 | 2.9 | 3800 | 0.3508 | 0.4489 |
| 0.2991 | 2.97 | 3900 | 0.3585 | 0.4356 |
| 0.1579 | 3.05 | 4000 | 0.3603 | 0.4326 |
| 0.2319 | 3.13 | 4100 | 0.3442 | 0.4201 |
| 0.1941 | 3.2 | 4200 | 0.3344 | 0.4116 |
| 0.2561 | 3.28 | 4300 | 0.3475 | 0.4200 |
| 0.3208 | 3.36 | 4400 | 0.3505 | 0.4089 |
| 0.2555 | 3.43 | 4500 | 0.3593 | 0.4271 |
| 0.1927 | 3.51 | 4600 | 0.3536 | 0.4299 |
| 0.1994 | 3.59 | 4700 | 0.3672 | 0.4400 |
| 0.1357 | 3.66 | 4800 | 0.3433 | 0.4223 |
| 0.2043 | 3.74 | 4900 | 0.3471 | 0.4226 |
| 0.194 | 3.81 | 5000 | 0.3380 | 0.4230 |
| 0.1779 | 3.89 | 5100 | 0.3400 | 0.4130 |
| 0.1934 | 3.97 | 5200 | 0.3438 | 0.4104 |
| 0.1432 | 4.04 | 5300 | 0.3632 | 0.4254 |
| 0.1642 | 4.12 | 5400 | 0.3425 | 0.4237 |
| 0.2208 | 4.2 | 5500 | 0.3580 | 0.4132 |
| 0.1923 | 4.27 | 5600 | 0.3469 | 0.4143 |
| 0.2084 | 4.35 | 5700 | 0.3619 | 0.4252 |
| 0.2484 | 4.42 | 5800 | 0.3452 | 0.4210 |
| 0.1899 | 4.5 | 5900 | 0.3465 | 0.4136 |
| 0.1253 | 4.58 | 6000 | 0.3625 | 0.4150 |
| 0.1353 | 4.65 | 6100 | 0.3415 | 0.4182 |
| 0.2264 | 4.73 | 6200 | 0.3446 | 0.4153 |
| 0.2016 | 4.81 | 6300 | 0.3343 | 0.4087 |
| 0.1634 | 4.88 | 6400 | 0.3500 | 0.4253 |
| 0.2517 | 4.96 | 6500 | 0.3453 | 0.4291 |
| 0.1826 | 5.03 | 6600 | 0.3442 | 0.4106 |
| 0.174 | 5.11 | 6700 | 0.3478 | 0.3999 |
| 0.271 | 5.19 | 6800 | 0.3423 | 0.4023 |
| 0.1812 | 5.26 | 6900 | 0.3679 | 0.4200 |
| 0.3 | 5.34 | 7000 | 0.3583 | 0.4191 |
| 0.2678 | 5.42 | 7100 | 0.3534 | 0.4141 |
| 0.236 | 5.49 | 7200 | 0.3361 | 0.4041 |
| 0.1558 | 5.57 | 7300 | 0.3495 | 0.4126 |
| 0.2603 | 5.64 | 7400 | 0.3359 | 0.3969 |
| 0.1285 | 5.72 | 7500 | 0.3296 | 0.3994 |
| 0.4608 | 5.8 | 7600 | 0.3453 | 0.3933 |
| 0.1516 | 5.87 | 7700 | 0.3509 | 0.4028 |
| 0.2655 | 5.95 | 7800 | 0.3607 | 0.4109 |
| 0.22 | 6.03 | 7900 | 0.3392 | 0.3850 |
| 0.0787 | 6.1 | 8000 | 0.3395 | 0.3842 |
| 0.1297 | 6.18 | 8100 | 0.3356 | 0.3822 |
| 0.1747 | 6.25 | 8200 | 0.3275 | 0.3874 |
| 0.1647 | 6.33 | 8300 | 0.3554 | 0.3941 |
| 0.1314 | 6.41 | 8400 | 0.3287 | 0.3826 |
| 0.1264 | 6.48 | 8500 | 0.3122 | 0.3876 |
| 0.1229 | 6.56 | 8600 | 0.3525 | 0.3994 |
| 0.108 | 6.64 | 8700 | 0.3387 | 0.3968 |
| 0.185 | 6.71 | 8800 | 0.3333 | 0.3840 |
| 0.0924 | 6.79 | 8900 | 0.3366 | 0.3827 |
| 0.1226 | 6.86 | 9000 | 0.3243 | 0.3788 |
| 0.2005 | 6.94 | 9100 | 0.3324 | 0.3765 |
| 0.133 | 7.02 | 9200 | 0.3294 | 0.3688 |
| 0.0633 | 7.09 | 9300 | 0.3279 | 0.3738 |
| 0.0593 | 7.17 | 9400 | 0.3311 | 0.3639 |
| 0.088 | 7.25 | 9500 | 0.3221 | 0.3765 |
| 0.1489 | 7.32 | 9600 | 0.3421 | 0.3788 |
| 0.1175 | 7.4 | 9700 | 0.3191 | 0.3786 |
| 0.0983 | 7.48 | 9800 | 0.3303 | 0.3764 |
| 0.1493 | 7.55 | 9900 | 0.3371 | 0.3836 |
| 0.1091 | 7.63 | 10000 | 0.3410 | 0.3739 |
| 0.1058 | 7.7 | 10100 | 0.3262 | 0.3730 |
| 0.0849 | 7.78 | 10200 | 0.3379 | 0.3812 |
| 0.1362 | 7.86 | 10300 | 0.3291 | 0.3781 |
| 0.1227 | 7.93 | 10400 | 0.3235 | 0.3760 |
| 0.1647 | 8.01 | 10500 | 0.3285 | 0.3686 |
| 0.1013 | 8.09 | 10600 | 0.3319 | 0.3729 |
| 0.1432 | 8.16 | 10700 | 0.3280 | 0.3731 |
| 0.1345 | 8.24 | 10800 | 0.3237 | 0.3707 |
| 0.0813 | 8.31 | 10900 | 0.3285 | 0.3748 |
| 0.1063 | 8.39 | 11000 | 0.3321 | 0.3748 |
| 0.1342 | 8.47 | 11100 | 0.3171 | 0.3647 |
| 0.1202 | 8.54 | 11200 | 0.3209 | 0.3636 |
| 0.0987 | 8.62 | 11300 | 0.3224 | 0.3625 |
| 0.1357 | 8.7 | 11400 | 0.3245 | 0.3646 |
| 0.1038 | 8.77 | 11500 | 0.3172 | 0.3702 |
| 0.0961 | 8.85 | 11600 | 0.3080 | 0.3611 |
| 0.1836 | 8.92 | 11700 | 0.3112 | 0.3681 |
| 0.0951 | 9.0 | 11800 | 0.3157 | 0.3649 |
| 0.1162 | 9.08 | 11900 | 0.3188 | 0.3714 |
| 0.1157 | 9.15 | 12000 | 0.3383 | 0.3775 |
| 0.1268 | 9.23 | 12100 | 0.3204 | 0.3752 |
| 0.1402 | 9.31 | 12200 | 0.3441 | 0.3707 |
| 0.1094 | 9.38 | 12300 | 0.3415 | 0.3675 |
| 0.1122 | 9.46 | 12400 | 0.3150 | 0.3596 |
| 0.0932 | 9.53 | 12500 | 0.3195 | 0.3561 |
| 0.1176 | 9.61 | 12600 | 0.3250 | 0.3675 |
| 0.1287 | 9.69 | 12700 | 0.3253 | 0.3615 |
| 0.0886 | 9.76 | 12800 | 0.3276 | 0.3636 |
| 0.1016 | 9.84 | 12900 | 0.3185 | 0.3592 |
| 0.0902 | 9.92 | 13000 | 0.3177 | 0.3643 |
| 0.1304 | 9.99 | 13100 | 0.3131 | 0.3530 |
| 0.099 | 10.07 | 13200 | 0.3094 | 0.3525 |
| 0.1142 | 10.14 | 13300 | 0.3298 | 0.3609 |
| 0.1836 | 10.22 | 13400 | 0.3213 | 0.3526 |
| 0.1533 | 10.3 | 13500 | 0.3163 | 0.3579 |
| 0.1436 | 10.37 | 13600 | 0.3352 | 0.3543 |
| 0.1215 | 10.45 | 13700 | 0.3355 | 0.3458 |
| 0.0971 | 10.53 | 13800 | 0.3232 | 0.3579 |
| 0.1215 | 10.6 | 13900 | 0.3168 | 0.3441 |
| 0.0906 | 10.68 | 14000 | 0.3266 | 0.3498 |
| 0.125 | 10.76 | 14100 | 0.3318 | 0.3414 |
| 0.0831 | 10.83 | 14200 | 0.3030 | 0.3480 |
| 0.1588 | 10.91 | 14300 | 0.3155 | 0.3455 |
| 0.1191 | 10.98 | 14400 | 0.3287 | 0.3487 |
| 0.074 | 11.06 | 14500 | 0.3176 | 0.3431 |
| 0.1075 | 11.14 | 14600 | 0.3219 | 0.3446 |
| 0.0679 | 11.21 | 14700 | 0.3158 | 0.3414 |
| 0.0789 | 11.29 | 14800 | 0.3305 | 0.3491 |
| 0.1426 | 11.37 | 14900 | 0.3281 | 0.3485 |
| 0.1154 | 11.44 | 15000 | 0.3368 | 0.3482 |
| 0.1313 | 11.52 | 15100 | 0.3285 | 0.3415 |
| 0.0786 | 11.59 | 15200 | 0.3138 | 0.3439 |
| 0.0595 | 11.67 | 15300 | 0.3135 | 0.3431 |
| 0.0868 | 11.75 | 15400 | 0.3049 | 0.3396 |
| 0.0812 | 11.82 | 15500 | 0.3050 | 0.3373 |
| 0.1199 | 11.9 | 15600 | 0.3238 | 0.3392 |
| 0.1243 | 11.98 | 15700 | 0.3123 | 0.3368 |
| 0.0663 | 12.05 | 15800 | 0.3226 | 0.3373 |
| 0.0285 | 12.13 | 15900 | 0.3260 | 0.3367 |
| 0.0607 | 12.2 | 16000 | 0.3236 | 0.3406 |
| 0.064 | 12.28 | 16100 | 0.3297 | 0.3357 |
| 0.0554 | 12.36 | 16200 | 0.3357 | 0.3383 |
| 0.0561 | 12.43 | 16300 | 0.3211 | 0.3387 |
| 0.0785 | 12.51 | 16400 | 0.3140 | 0.3386 |
| 0.0539 | 12.59 | 16500 | 0.3130 | 0.3361 |
| 0.0873 | 12.66 | 16600 | 0.3244 | 0.3344 |
| 0.0774 | 12.74 | 16700 | 0.3128 | 0.3274 |
| 0.0853 | 12.81 | 16800 | 0.3185 | 0.3395 |
| 0.0701 | 12.89 | 16900 | 0.3244 | 0.3327 |
| 0.0486 | 12.97 | 17000 | 0.3100 | 0.3317 |
| 0.1087 | 13.04 | 17100 | 0.3351 | 0.3327 |
| 0.0716 | 13.12 | 17200 | 0.3474 | 0.3383 |
| 0.0653 | 13.2 | 17300 | 0.3361 | 0.3364 |
| 0.0936 | 13.27 | 17400 | 0.3423 | 0.3352 |
| 0.0761 | 13.35 | 17500 | 0.3261 | 0.3304 |
| 0.0723 | 13.42 | 17600 | 0.3298 | 0.3333 |
| 0.0756 | 13.5 | 17700 | 0.3282 | 0.3367 |
| 0.058 | 13.58 | 17800 | 0.3386 | 0.3303 |
| 0.0619 | 13.65 | 17900 | 0.3354 | 0.3306 |
| 0.081 | 13.73 | 18000 | 0.3413 | 0.3317 |
| 0.0893 | 13.81 | 18100 | 0.3257 | 0.3278 |
| 0.0858 | 13.88 | 18200 | 0.3312 | 0.3255 |
| 0.0756 | 13.96 | 18300 | 0.3279 | 0.3326 |
| 0.0946 | 14.04 | 18400 | 0.3412 | 0.3272 |
| 0.1452 | 14.11 | 18500 | 0.3394 | 0.3266 |
| 0.0772 | 14.19 | 18600 | 0.3271 | 0.3261 |
| 0.0748 | 14.26 | 18700 | 0.3338 | 0.3272 |
| 0.0789 | 14.34 | 18800 | 0.3461 | 0.3254 |
| 0.0967 | 14.42 | 18900 | 0.3163 | 0.3250 |
| 0.0938 | 14.49 | 19000 | 0.3273 | 0.3261 |
| 0.1134 | 14.57 | 19100 | 0.3301 | 0.3284 |
| 0.1051 | 14.65 | 19200 | 0.3187 | 0.3215 |
| 0.0936 | 14.72 | 19300 | 0.3211 | 0.3197 |
| 0.0528 | 14.8 | 19400 | 0.3381 | 0.3270 |
| 0.1497 | 14.87 | 19500 | 0.3291 | 0.3235 |
| 0.1168 | 14.95 | 19600 | 0.3290 | 0.3238 |
| 0.028 | 15.03 | 19700 | 0.3333 | 0.3209 |
| 0.0773 | 15.1 | 19800 | 0.3359 | 0.3206 |
| 0.0972 | 15.18 | 19900 | 0.3262 | 0.3163 |
| 0.0391 | 15.26 | 20000 | 0.3335 | 0.3180 |
| 0.0571 | 15.33 | 20100 | 0.3445 | 0.3198 |
| 0.0365 | 15.41 | 20200 | 0.3318 | 0.3170 |
| 0.0535 | 15.48 | 20300 | 0.3257 | 0.3147 |
| 0.0739 | 15.56 | 20400 | 0.3359 | 0.3136 |
| 0.0753 | 15.64 | 20500 | 0.3216 | 0.3195 |
| 0.1507 | 15.71 | 20600 | 0.3326 | 0.3154 |
| 0.062 | 15.79 | 20700 | 0.3310 | 0.3164 |
| 0.0595 | 15.87 | 20800 | 0.3134 | 0.3162 |
| 0.0456 | 15.94 | 20900 | 0.3146 | 0.3127 |
| 0.0977 | 16.02 | 21000 | 0.3328 | 0.3117 |
| 0.036 | 16.09 | 21100 | 0.3266 | 0.3134 |
| 0.0308 | 16.17 | 21200 | 0.3306 | 0.3136 |
| 0.0612 | 16.25 | 21300 | 0.3207 | 0.3160 |
| 0.0269 | 16.32 | 21400 | 0.3429 | 0.3143 |
| 0.0897 | 16.4 | 21500 | 0.3355 | 0.3111 |
| 0.0458 | 16.48 | 21600 | 0.3238 | 0.3065 |
| 0.0155 | 16.55 | 21700 | 0.3167 | 0.3042 |
| 0.0519 | 16.63 | 21800 | 0.3296 | 0.3099 |
| 0.0807 | 16.7 | 21900 | 0.3250 | 0.3048 |
| 0.0406 | 16.78 | 22000 | 0.3283 | 0.3087 |
| 0.0773 | 16.86 | 22100 | 0.3217 | 0.3047 |
| 0.1027 | 16.93 | 22200 | 0.3279 | 0.3108 |
| 0.0315 | 17.01 | 22300 | 0.3173 | 0.3058 |
| 0.0457 | 17.09 | 22400 | 0.3387 | 0.3085 |
| 0.0516 | 17.16 | 22500 | 0.3309 | 0.3050 |
| 0.0413 | 17.24 | 22600 | 0.3363 | 0.3067 |
| 0.0601 | 17.32 | 22700 | 0.3325 | 0.3048 |
| 0.0435 | 17.39 | 22800 | 0.3298 | 0.3058 |
| 0.0571 | 17.47 | 22900 | 0.3244 | 0.3033 |
| 0.0656 | 17.54 | 23000 | 0.3350 | 0.3056 |
| 0.0485 | 17.62 | 23100 | 0.3406 | 0.3051 |
| 0.0619 | 17.7 | 23200 | 0.3268 | 0.3033 |
| 0.0495 | 17.77 | 23300 | 0.3268 | 0.3031 |
| 0.0416 | 17.85 | 23400 | 0.3268 | 0.3038 |
| 0.0646 | 17.93 | 23500 | 0.3314 | 0.3009 |
| 0.0294 | 18.0 | 23600 | 0.3251 | 0.3028 |
| 0.0372 | 18.08 | 23700 | 0.3364 | 0.2962 |
| 0.04 | 18.15 | 23800 | 0.3358 | 0.2967 |
| 0.0367 | 18.23 | 23900 | 0.3317 | 0.3031 |
| 0.0312 | 18.31 | 24000 | 0.3272 | 0.2998 |
| 0.0419 | 18.38 | 24100 | 0.3358 | 0.2996 |
| 0.0477 | 18.46 | 24200 | 0.3283 | 0.2996 |
| 0.0256 | 18.54 | 24300 | 0.3310 | 0.2995 |
| 0.0269 | 18.61 | 24400 | 0.3325 | 0.2997 |
| 0.0309 | 18.69 | 24500 | 0.3345 | 0.2974 |
| 0.0441 | 18.76 | 24600 | 0.3345 | 0.3003 |
| 0.0496 | 18.84 | 24700 | 0.3396 | 0.2985 |
| 0.0425 | 18.92 | 24800 | 0.3425 | 0.2965 |
| 0.0196 | 18.99 | 24900 | 0.3373 | 0.2964 |
| 0.0348 | 19.07 | 25000 | 0.3361 | 0.2955 |
| 0.0466 | 19.15 | 25100 | 0.3328 | 0.2959 |
| 0.0422 | 19.22 | 25200 | 0.3343 | 0.2964 |
| 0.0271 | 19.3 | 25300 | 0.3369 | 0.2945 |
| 0.053 | 19.37 | 25400 | 0.3330 | 0.2953 |
| 0.0662 | 19.45 | 25500 | 0.3343 | 0.2958 |
| 0.0718 | 19.53 | 25600 | 0.3330 | 0.2952 |
| 0.0212 | 19.6 | 25700 | 0.3352 | 0.2940 |
| 0.0971 | 19.68 | 25800 | 0.3374 | 0.2935 |
| 0.0413 | 19.76 | 25900 | 0.3362 | 0.2933 |
| 0.0477 | 19.83 | 26000 | 0.3356 | 0.2940 |
| 0.1068 | 19.91 | 26100 | 0.3365 | 0.2937 |
| 0.108 | 19.98 | 26200 | 0.3366 | 0.2935 |
### Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1
- Datasets 2.13.1
- Tokenizers 0.13.2
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