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kblab-voxrex-wav2vec2-large-cv8-da

Automatic Speech Recognition
Transformers
PyTorch
Danish
wav2vec2
Eval Results
Inference Endpoints
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+ ---
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+ license: cc0-1.0
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - common_voice
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+ model-index:
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+ - name: kblab-voxrex-wav2vec2-large-cv8-da
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # kblab-voxrex-wav2vec2-large-cv8-da
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+
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+ This model is a fine-tuned version of [KBLab/wav2vec2-large-voxrex](https://huggingface.co/KBLab/wav2vec2-large-voxrex) on the common_voice dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 334.1232
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+ - Wer: 0.3729
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 4e-05
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+ - train_batch_size: 4
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+ - eval_batch_size: 8
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+ - seed: 4242
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+ - gradient_accumulation_steps: 8
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+ - total_train_batch_size: 32
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 500
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+ - num_epochs: 500
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Wer |
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+ |:-------------:|:------:|:-----:|:---------------:|:------:|
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+ | 745.9947 | 5.55 | 300 | 1354.9309 | 1.0 |
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+ | 576.053 | 11.11 | 600 | 1264.9503 | 1.0 |
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+ | 506.6065 | 16.66 | 900 | 999.9504 | 0.9999 |
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+ | 278.9146 | 22.22 | 1200 | 497.2084 | 0.8253 |
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+ | 203.6943 | 27.77 | 1500 | 382.0594 | 0.6598 |
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+ | 164.3587 | 33.33 | 1800 | 332.7126 | 0.5789 |
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+ | 136.6555 | 38.88 | 2100 | 314.8907 | 0.5433 |
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+ | 116.4133 | 44.44 | 2400 | 298.0489 | 0.5105 |
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+ | 103.4391 | 49.99 | 2700 | 288.4926 | 0.4862 |
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+ | 94.8171 | 55.55 | 3000 | 286.2634 | 0.4675 |
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+ | 83.2515 | 61.11 | 3300 | 282.2958 | 0.4596 |
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+ | 75.3823 | 66.66 | 3600 | 283.7801 | 0.4481 |
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+ | 68.4964 | 72.22 | 3900 | 288.9401 | 0.4460 |
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+ | 64.664 | 77.77 | 4200 | 286.0048 | 0.4411 |
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+ | 60.8176 | 83.33 | 4500 | 281.5687 | 0.4313 |
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+ | 55.4021 | 88.88 | 4800 | 285.4101 | 0.4250 |
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+ | 52.1835 | 94.44 | 5100 | 289.8307 | 0.4223 |
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+ | 50.4828 | 99.99 | 5400 | 283.2961 | 0.4138 |
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+ | 48.3316 | 105.55 | 5700 | 291.5920 | 0.4116 |
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+ | 43.5322 | 111.11 | 6000 | 291.0108 | 0.4129 |
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+ | 41.9436 | 116.66 | 6300 | 289.5014 | 0.4082 |
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+ | 38.9519 | 122.22 | 6600 | 292.2263 | 0.4102 |
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+ | 39.0257 | 127.77 | 6900 | 299.3404 | 0.4016 |
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+ | 37.7255 | 133.33 | 7200 | 302.4544 | 0.3999 |
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+ | 35.9706 | 138.88 | 7500 | 294.0447 | 0.3934 |
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+ | 34.1693 | 144.44 | 7800 | 295.0625 | 0.3936 |
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+ | 32.4428 | 149.99 | 8100 | 300.1613 | 0.3935 |
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+ | 33.4516 | 155.55 | 8400 | 310.9324 | 0.3951 |
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+ | 31.039 | 161.11 | 8700 | 313.7309 | 0.3921 |
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+ | 29.4764 | 166.66 | 9000 | 307.3336 | 0.3976 |
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+ | 29.4936 | 172.22 | 9300 | 304.8356 | 0.3958 |
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+ | 27.3962 | 177.77 | 9600 | 309.1968 | 0.3895 |
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+ | 28.9029 | 183.33 | 9900 | 313.4612 | 0.3899 |
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+ | 26.0951 | 188.88 | 10200 | 310.5530 | 0.3862 |
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+ | 26.339 | 194.44 | 10500 | 312.8733 | 0.3850 |
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+ | 25.0828 | 199.99 | 10800 | 319.1792 | 0.3904 |
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+ | 25.2904 | 205.55 | 11100 | 305.1705 | 0.3896 |
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+ | 24.3586 | 211.11 | 11400 | 316.6768 | 0.3895 |
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+ | 22.0152 | 216.66 | 11700 | 325.8116 | 0.3890 |
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+ | 23.443 | 222.22 | 12000 | 315.7543 | 0.3805 |
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+ | 23.6808 | 227.77 | 12300 | 324.8992 | 0.3831 |
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+ | 22.6985 | 233.33 | 12600 | 321.0045 | 0.3814 |
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+ | 21.3545 | 238.88 | 12900 | 323.3702 | 0.3843 |
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+ | 20.9784 | 244.44 | 13200 | 334.0336 | 0.3844 |
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+ | 20.1037 | 249.99 | 13500 | 316.2501 | 0.3764 |
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+ | 20.2854 | 255.55 | 13800 | 322.2803 | 0.3768 |
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+ | 19.4469 | 261.11 | 14100 | 326.5724 | 0.3760 |
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+ | 20.1176 | 266.66 | 14400 | 322.7105 | 0.3752 |
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+ | 19.1208 | 272.22 | 14700 | 323.2078 | 0.3766 |
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+ | 20.024 | 277.77 | 15000 | 317.7683 | 0.3696 |
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+ | 18.8389 | 283.33 | 15300 | 323.7159 | 0.3702 |
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+ | 19.5328 | 288.88 | 15600 | 324.3281 | 0.3713 |
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+ | 18.4362 | 294.44 | 15900 | 329.0278 | 0.3749 |
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+ | 16.8288 | 299.99 | 16200 | 327.6952 | 0.3727 |
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+ | 17.6299 | 305.55 | 16500 | 334.1232 | 0.3729 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.16.2
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+ - Pytorch 1.10.2+cu102
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+ - Datasets 1.18.3
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+ - Tokenizers 0.11.0