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library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: ssc-lth-model
results: []
---
<!-- 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. -->
# ssc-lth-model
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5683
- Cer: 0.3085
- Wer: 0.7821
## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Cer | Wer |
|:-------------:|:-------:|:-----:|:---------------:|:------:|:------:|
| 5.7582 | 0.1546 | 100 | 3.1629 | 0.9943 | 1.0 |
| 3.4065 | 0.3091 | 200 | 3.1093 | 0.9943 | 1.0 |
| 3.3576 | 0.4637 | 300 | 3.0748 | 0.9943 | 1.0 |
| 3.1832 | 0.6182 | 400 | 3.0296 | 0.9943 | 1.0 |
| 3.1613 | 0.7728 | 500 | 2.9966 | 0.9943 | 1.0 |
| 3.1446 | 0.9274 | 600 | 3.0421 | 0.9943 | 1.0 |
| 3.1082 | 1.0819 | 700 | 3.0424 | 0.9943 | 1.0 |
| 3.0153 | 1.2365 | 800 | 2.8610 | 0.9943 | 1.0 |
| 2.8793 | 1.3910 | 900 | 2.8591 | 0.8887 | 1.0 |
| 2.7603 | 1.5456 | 1000 | 2.5400 | 0.8918 | 1.0 |
| 2.6694 | 1.7002 | 1100 | 2.4441 | 0.8234 | 1.0 |
| 2.4981 | 1.8547 | 1200 | 2.1997 | 0.7659 | 1.0 |
| 2.3687 | 2.0093 | 1300 | 2.0222 | 0.7077 | 1.0 |
| 2.3179 | 2.1638 | 1400 | 1.9736 | 0.6633 | 1.0 |
| 2.2323 | 2.3184 | 1500 | 2.0691 | 0.5410 | 0.9733 |
| 2.1893 | 2.4730 | 1600 | 1.8443 | 0.5961 | 0.9948 |
| 2.1184 | 2.6275 | 1700 | 1.8428 | 0.5332 | 0.9794 |
| 2.0585 | 2.7821 | 1800 | 1.7327 | 0.5545 | 0.9920 |
| 2.0365 | 2.9366 | 1900 | 1.7461 | 0.5172 | 0.9742 |
| 1.9224 | 3.0912 | 2000 | 1.6829 | 0.4921 | 0.9501 |
| 1.9396 | 3.2457 | 2100 | 1.6787 | 0.4800 | 0.9399 |
| 1.9326 | 3.4003 | 2200 | 1.6375 | 0.5063 | 0.9644 |
| 1.8535 | 3.5549 | 2300 | 1.6068 | 0.4837 | 0.9530 |
| 1.859 | 3.7094 | 2400 | 1.5812 | 0.4838 | 0.9517 |
| 1.8666 | 3.8640 | 2500 | 1.6099 | 0.4670 | 0.9356 |
| 1.8084 | 4.0185 | 2600 | 1.5219 | 0.4707 | 0.9381 |
| 1.7369 | 4.1731 | 2700 | 1.5108 | 0.4377 | 0.9229 |
| 1.7619 | 4.3277 | 2800 | 1.4897 | 0.4434 | 0.9216 |
| 1.7268 | 4.4822 | 2900 | 1.5166 | 0.4525 | 0.9377 |
| 1.6908 | 4.6368 | 3000 | 1.5185 | 0.4541 | 0.9247 |
| 1.7478 | 4.7913 | 3100 | 1.4809 | 0.4382 | 0.9254 |
| 1.7223 | 4.9459 | 3200 | 1.4538 | 0.4354 | 0.9231 |
| 1.6529 | 5.1005 | 3300 | 1.4845 | 0.4355 | 0.9185 |
| 1.633 | 5.2550 | 3400 | 1.4235 | 0.4358 | 0.9252 |
| 1.6486 | 5.4096 | 3500 | 1.3745 | 0.4156 | 0.9040 |
| 1.6362 | 5.5641 | 3600 | 1.4383 | 0.4047 | 0.9683 |
| 1.552 | 5.7187 | 3700 | 1.4306 | 0.4195 | 0.9150 |
| 1.5794 | 5.8733 | 3800 | 1.4064 | 0.4153 | 0.9155 |
| 1.5882 | 6.0278 | 3900 | 1.4026 | 0.4055 | 0.9205 |
| 1.4888 | 6.1824 | 4000 | 1.4291 | 0.4131 | 0.9315 |
| 1.5515 | 6.3369 | 4100 | 1.4047 | 0.4018 | 0.9229 |
| 1.5229 | 6.4915 | 4200 | 1.3459 | 0.3977 | 0.8988 |
| 1.5235 | 6.6461 | 4300 | 1.3754 | 0.3957 | 0.9233 |
| 1.4919 | 6.8006 | 4400 | 1.3355 | 0.3897 | 0.9222 |
| 1.5215 | 6.9552 | 4500 | 1.3391 | 0.3882 | 0.9048 |
| 1.4768 | 7.1097 | 4600 | 1.3710 | 0.3982 | 0.8937 |
| 1.4441 | 7.2643 | 4700 | 1.3814 | 0.3961 | 0.9112 |
| 1.3782 | 7.4189 | 4800 | 1.3806 | 0.4105 | 0.9028 |
| 1.4264 | 7.5734 | 4900 | 1.3845 | 0.3897 | 0.9491 |
| 1.4418 | 7.7280 | 5000 | 1.2996 | 0.3800 | 0.8863 |
| 1.4022 | 7.8825 | 5100 | 1.3480 | 0.3957 | 0.8869 |
| 1.4414 | 8.0371 | 5200 | 1.3391 | 0.3847 | 0.9246 |
| 1.3637 | 8.1917 | 5300 | 1.3786 | 0.3991 | 0.8862 |
| 1.365 | 8.3462 | 5400 | 1.2898 | 0.3729 | 0.8711 |
| 1.3352 | 8.5008 | 5500 | 1.2853 | 0.3774 | 0.8765 |
| 1.3346 | 8.6553 | 5600 | 1.3410 | 0.3974 | 0.8972 |
| 1.3163 | 8.8099 | 5700 | 1.3299 | 0.3836 | 0.9205 |
| 1.38 | 8.9645 | 5800 | 1.4417 | 0.3892 | 0.9467 |
| 1.3366 | 9.1190 | 5900 | 1.4005 | 0.3906 | 0.8904 |
| 1.287 | 9.2736 | 6000 | 1.3038 | 0.3713 | 0.8920 |
| 1.2572 | 9.4281 | 6100 | 1.3145 | 0.3853 | 0.8755 |
| 1.2785 | 9.5827 | 6200 | 1.3774 | 0.3848 | 0.8795 |
| 1.237 | 9.7372 | 6300 | 1.3252 | 0.3853 | 0.8768 |
| 1.2779 | 9.8918 | 6400 | 1.2781 | 0.3737 | 0.8769 |
| 1.2935 | 10.0464 | 6500 | 1.3950 | 0.3881 | 0.8870 |
| 1.1689 | 10.2009 | 6600 | 1.3417 | 0.3744 | 0.8764 |
| 1.2232 | 10.3555 | 6700 | 1.3423 | 0.3755 | 0.8663 |
| 1.2236 | 10.5100 | 6800 | 1.2751 | 0.3684 | 0.8837 |
| 1.2102 | 10.6646 | 6900 | 1.2827 | 0.3716 | 0.8638 |
| 1.2025 | 10.8192 | 7000 | 1.3115 | 0.3707 | 0.8959 |
| 1.2348 | 10.9737 | 7100 | 1.3197 | 0.3633 | 0.8900 |
| 1.1198 | 11.1283 | 7200 | 1.3162 | 0.3682 | 0.8566 |
| 1.1254 | 11.2828 | 7300 | 1.3437 | 0.3709 | 0.8776 |
| 1.1438 | 11.4374 | 7400 | 1.3546 | 0.3753 | 0.8628 |
| 1.1528 | 11.5920 | 7500 | 1.2441 | 0.3541 | 0.8558 |
| 1.1301 | 11.7465 | 7600 | 1.2736 | 0.3697 | 0.8635 |
| 1.1229 | 11.9011 | 7700 | 1.2383 | 0.3597 | 0.8637 |
| 1.1234 | 12.0556 | 7800 | 1.2476 | 0.3583 | 0.8518 |
| 1.0714 | 12.2102 | 7900 | 1.2173 | 0.3515 | 0.8411 |
| 1.0748 | 12.3648 | 8000 | 1.1947 | 0.3478 | 0.8346 |
| 1.0588 | 12.5193 | 8100 | 1.3123 | 0.3533 | 0.8537 |
| 1.0727 | 12.6739 | 8200 | 1.2479 | 0.3562 | 0.8472 |
| 1.0688 | 12.8284 | 8300 | 1.2803 | 0.3600 | 0.8502 |
| 1.1059 | 12.9830 | 8400 | 1.2793 | 0.3529 | 0.8476 |
| 1.0258 | 13.1376 | 8500 | 1.2690 | 0.3636 | 0.8521 |
| 1.012 | 13.2921 | 8600 | 1.2987 | 0.3478 | 0.8704 |
| 0.9649 | 13.4467 | 8700 | 1.4050 | 0.3718 | 0.8624 |
| 0.9875 | 13.6012 | 8800 | 1.2196 | 0.3451 | 0.8436 |
| 1.0292 | 13.7558 | 8900 | 1.2596 | 0.3529 | 0.8320 |
| 1.0342 | 13.9104 | 9000 | 1.2486 | 0.3464 | 0.8497 |
| 1.0011 | 14.0649 | 9100 | 1.2429 | 0.3533 | 0.8423 |
| 0.9401 | 14.2195 | 9200 | 1.3330 | 0.3603 | 0.8569 |
| 0.9597 | 14.3740 | 9300 | 1.2858 | 0.3636 | 0.8501 |
| 0.9457 | 14.5286 | 9400 | 1.1997 | 0.3444 | 0.8472 |
| 0.9661 | 14.6832 | 9500 | 1.1897 | 0.3401 | 0.8425 |
| 0.9555 | 14.8377 | 9600 | 1.2808 | 0.3527 | 0.8334 |
| 0.9833 | 14.9923 | 9700 | 1.2827 | 0.3486 | 0.8392 |
| 0.8874 | 15.1468 | 9800 | 1.4258 | 0.3675 | 0.8566 |
| 0.8955 | 15.3014 | 9900 | 1.2527 | 0.3462 | 0.8229 |
| 0.8936 | 15.4560 | 10000 | 1.2336 | 0.3363 | 0.8394 |
| 0.8948 | 15.6105 | 10100 | 1.2048 | 0.3366 | 0.8244 |
| 0.9023 | 15.7651 | 10200 | 1.3404 | 0.3410 | 0.8237 |
| 0.9056 | 15.9196 | 10300 | 1.3217 | 0.3543 | 0.8379 |
| 0.904 | 16.0742 | 10400 | 1.3742 | 0.3638 | 0.8376 |
| 0.7977 | 16.2287 | 10500 | 1.2720 | 0.3305 | 0.8096 |
| 0.8473 | 16.3833 | 10600 | 1.3408 | 0.3376 | 0.8546 |
| 0.8579 | 16.5379 | 10700 | 1.2352 | 0.3421 | 0.8193 |
| 0.8524 | 16.6924 | 10800 | 1.3313 | 0.3500 | 0.8385 |
| 0.8388 | 16.8470 | 10900 | 1.2586 | 0.3315 | 0.8296 |
| 0.8291 | 17.0015 | 11000 | 1.2370 | 0.3517 | 0.8368 |
| 0.7695 | 17.1561 | 11100 | 1.2832 | 0.3339 | 0.8271 |
| 0.7844 | 17.3107 | 11200 | 1.2764 | 0.3453 | 0.8468 |
| 0.7764 | 17.4652 | 11300 | 1.2639 | 0.3428 | 0.8409 |
| 0.8082 | 17.6198 | 11400 | 1.2235 | 0.3359 | 0.8198 |
| 0.7982 | 17.7743 | 11500 | 1.2658 | 0.3352 | 0.8140 |
| 0.7763 | 17.9289 | 11600 | 1.2210 | 0.3287 | 0.8186 |
| 0.7947 | 18.0835 | 11700 | 1.2735 | 0.3292 | 0.7998 |
| 0.7261 | 18.2380 | 11800 | 1.2937 | 0.3400 | 0.8121 |
| 0.745 | 18.3926 | 11900 | 1.2504 | 0.3385 | 0.8136 |
| 0.7626 | 18.5471 | 12000 | 1.2307 | 0.3260 | 0.8023 |
| 0.725 | 18.7017 | 12100 | 1.2764 | 0.3369 | 0.8021 |
| 0.7459 | 18.8563 | 12200 | 1.2189 | 0.3309 | 0.8020 |
| 0.7395 | 19.0108 | 12300 | 1.2120 | 0.3197 | 0.7927 |
| 0.689 | 19.1654 | 12400 | 1.2412 | 0.3241 | 0.7974 |
| 0.6776 | 19.3199 | 12500 | 1.1921 | 0.3202 | 0.7936 |
| 0.6629 | 19.4745 | 12600 | 1.2220 | 0.3220 | 0.7943 |
| 0.7292 | 19.6291 | 12700 | 1.2844 | 0.3186 | 0.7953 |
| 0.7135 | 19.7836 | 12800 | 1.2520 | 0.3211 | 0.7932 |
| 0.7042 | 19.9382 | 12900 | 1.2142 | 0.3127 | 0.7783 |
| 0.6766 | 20.0927 | 13000 | 1.2213 | 0.3176 | 0.7884 |
| 0.6471 | 20.2473 | 13100 | 1.3010 | 0.3232 | 0.8033 |
| 0.6842 | 20.4019 | 13200 | 1.3410 | 0.3273 | 0.8023 |
| 0.6308 | 20.5564 | 13300 | 1.2506 | 0.3159 | 0.7932 |
| 0.6551 | 20.7110 | 13400 | 1.3087 | 0.3197 | 0.7979 |
| 0.6413 | 20.8655 | 13500 | 1.2666 | 0.3168 | 0.7988 |
| 0.6279 | 21.0201 | 13600 | 1.3987 | 0.3141 | 0.7816 |
| 0.6173 | 21.1747 | 13700 | 1.3371 | 0.3125 | 0.7974 |
| 0.5904 | 21.3292 | 13800 | 1.3081 | 0.3274 | 0.8015 |
| 0.6126 | 21.4838 | 13900 | 1.3683 | 0.3247 | 0.8083 |
| 0.6055 | 21.6383 | 14000 | 1.3113 | 0.3157 | 0.7977 |
| 0.6225 | 21.7929 | 14100 | 1.2706 | 0.3110 | 0.7865 |
| 0.6007 | 21.9474 | 14200 | 1.3128 | 0.3264 | 0.7931 |
| 0.5837 | 22.1020 | 14300 | 1.3846 | 0.3198 | 0.7923 |
| 0.5531 | 22.2566 | 14400 | 1.3394 | 0.3265 | 0.8053 |
| 0.5748 | 22.4111 | 14500 | 1.3888 | 0.3220 | 0.7889 |
| 0.555 | 22.5657 | 14600 | 1.3188 | 0.3242 | 0.7950 |
| 0.5632 | 22.7202 | 14700 | 1.3423 | 0.3216 | 0.7884 |
| 0.5717 | 22.8748 | 14800 | 1.3724 | 0.3133 | 0.8009 |
| 0.5513 | 23.0294 | 14900 | 1.3964 | 0.3183 | 0.7924 |
| 0.5324 | 23.1839 | 15000 | 1.4374 | 0.3187 | 0.8119 |
| 0.5538 | 23.3385 | 15100 | 1.3371 | 0.3176 | 0.7888 |
| 0.5098 | 23.4930 | 15200 | 1.3456 | 0.3139 | 0.7812 |
| 0.5437 | 23.6476 | 15300 | 1.3673 | 0.3183 | 0.7910 |
| 0.5621 | 23.8022 | 15400 | 1.3920 | 0.3204 | 0.7893 |
| 0.5265 | 23.9567 | 15500 | 1.3835 | 0.3211 | 0.7995 |
| 0.4964 | 24.1113 | 15600 | 1.3911 | 0.3153 | 0.7877 |
| 0.489 | 24.2658 | 15700 | 1.4370 | 0.3224 | 0.8030 |
| 0.4907 | 24.4204 | 15800 | 1.4016 | 0.3268 | 0.7973 |
| 0.49 | 24.5750 | 15900 | 1.4152 | 0.3175 | 0.7901 |
| 0.5104 | 24.7295 | 16000 | 1.4569 | 0.3200 | 0.7846 |
| 0.5075 | 24.8841 | 16100 | 1.4782 | 0.3175 | 0.7957 |
| 0.4939 | 25.0386 | 16200 | 1.4216 | 0.3155 | 0.7935 |
| 0.4501 | 25.1932 | 16300 | 1.4857 | 0.3234 | 0.7995 |
| 0.4498 | 25.3478 | 16400 | 1.4586 | 0.3161 | 0.7969 |
| 0.4521 | 25.5023 | 16500 | 1.5067 | 0.3195 | 0.7895 |
| 0.4624 | 25.6569 | 16600 | 1.4472 | 0.3151 | 0.7927 |
| 0.4881 | 25.8114 | 16700 | 1.4872 | 0.3175 | 0.7999 |
| 0.4802 | 25.9660 | 16800 | 1.4425 | 0.3118 | 0.7969 |
| 0.4441 | 26.1206 | 16900 | 1.5231 | 0.3177 | 0.8007 |
| 0.4641 | 26.2751 | 17000 | 1.4957 | 0.3152 | 0.7935 |
| 0.4417 | 26.4297 | 17100 | 1.5059 | 0.3151 | 0.7932 |
| 0.4492 | 26.5842 | 17200 | 1.4759 | 0.3136 | 0.7847 |
| 0.4443 | 26.7388 | 17300 | 1.5226 | 0.3121 | 0.7882 |
| 0.4635 | 26.8934 | 17400 | 1.4899 | 0.3090 | 0.7768 |
| 0.4432 | 27.0479 | 17500 | 1.5173 | 0.3156 | 0.7818 |
| 0.4349 | 27.2025 | 17600 | 1.5088 | 0.3122 | 0.7817 |
| 0.4235 | 27.3570 | 17700 | 1.5343 | 0.3149 | 0.8004 |
| 0.4174 | 27.5116 | 17800 | 1.5429 | 0.3090 | 0.7906 |
| 0.4293 | 27.6662 | 17900 | 1.5188 | 0.3122 | 0.7838 |
| 0.4164 | 27.8207 | 18000 | 1.5407 | 0.3090 | 0.7850 |
| 0.4202 | 27.9753 | 18100 | 1.5115 | 0.3092 | 0.7797 |
| 0.393 | 28.1298 | 18200 | 1.5165 | 0.3082 | 0.7799 |
| 0.3997 | 28.2844 | 18300 | 1.5150 | 0.3093 | 0.7825 |
| 0.4368 | 28.4389 | 18400 | 1.5381 | 0.3092 | 0.7765 |
| 0.372 | 28.5935 | 18500 | 1.5266 | 0.3096 | 0.7876 |
| 0.4138 | 28.7481 | 18600 | 1.5435 | 0.3085 | 0.7823 |
| 0.4082 | 28.9026 | 18700 | 1.5375 | 0.3079 | 0.7825 |
| 0.4009 | 29.0572 | 18800 | 1.5643 | 0.3098 | 0.7856 |
| 0.3883 | 29.2117 | 18900 | 1.5731 | 0.3063 | 0.7829 |
| 0.3836 | 29.3663 | 19000 | 1.5718 | 0.3073 | 0.7820 |
| 0.3939 | 29.5209 | 19100 | 1.5822 | 0.3079 | 0.7827 |
| 0.3915 | 29.6754 | 19200 | 1.5766 | 0.3087 | 0.7829 |
| 0.3958 | 29.8300 | 19300 | 1.5688 | 0.3086 | 0.7827 |
| 0.4069 | 29.9845 | 19400 | 1.5683 | 0.3085 | 0.7821 |
### Framework versions
- Transformers 4.57.2
- Pytorch 2.9.1+cu128
- Datasets 3.6.0
- Tokenizers 0.22.0
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