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--- |
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license: apache-2.0 |
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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: wav2vec2-xls-r-300m-cv8-da |
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results: [] |
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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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# wav2vec2-xls-r-300m-cv8-da |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 287.3684 |
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- Wer: 0.2978 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:------:|:-----:|:---------------:|:------:| |
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| 736.2597 | 5.55 | 300 | 1418.4758 | 1.0 | |
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| 577.3605 | 11.11 | 600 | 1267.1588 | 1.0 | |
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| 476.434 | 16.66 | 900 | 842.5760 | 1.0028 | |
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| 215.5165 | 22.22 | 1200 | 356.9064 | 0.6405 | |
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| 138.4598 | 27.77 | 1500 | 256.0349 | 0.4889 | |
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| 104.3224 | 33.33 | 1800 | 228.9147 | 0.4435 | |
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| 82.2922 | 38.88 | 2100 | 208.3896 | 0.4134 | |
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| 68.0471 | 44.44 | 2400 | 205.3142 | 0.3976 | |
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| 57.6613 | 49.99 | 2700 | 208.4677 | 0.3935 | |
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| 52.6747 | 55.55 | 3000 | 213.9339 | 0.3928 | |
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| 43.4302 | 61.11 | 3300 | 212.9035 | 0.3808 | |
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| 40.6623 | 66.66 | 3600 | 221.2281 | 0.3850 | |
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| 34.9752 | 72.22 | 3900 | 224.3349 | 0.3795 | |
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| 33.6799 | 77.77 | 4200 | 218.9585 | 0.3696 | |
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| 31.5797 | 83.33 | 4500 | 211.9424 | 0.3713 | |
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| 28.2278 | 88.88 | 4800 | 226.6527 | 0.3705 | |
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| 26.6871 | 94.44 | 5100 | 227.9236 | 0.3689 | |
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| 25.8799 | 99.99 | 5400 | 227.0796 | 0.3653 | |
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| 25.0987 | 105.55 | 5700 | 231.7458 | 0.3640 | |
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| 22.328 | 111.11 | 6000 | 236.6981 | 0.3644 | |
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| 21.8799 | 116.66 | 6300 | 219.9040 | 0.3573 | |
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| 20.1069 | 122.22 | 6600 | 230.2603 | 0.3592 | |
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| 20.8641 | 127.77 | 6900 | 248.2307 | 0.3638 | |
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| 18.6306 | 133.33 | 7200 | 239.0962 | 0.3583 | |
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| 18.2617 | 138.88 | 7500 | 245.4144 | 0.3549 | |
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| 17.5175 | 144.44 | 7800 | 258.2551 | 0.3617 | |
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| 56.1866 | 149.99 | 8100 | 278.0422 | 0.3384 | |
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| 28.7438 | 155.55 | 8400 | 271.7619 | 0.3107 | |
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| 23.462 | 161.11 | 8700 | 279.4823 | 0.3091 | |
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| 20.5816 | 166.66 | 9000 | 274.7589 | 0.3070 | |
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| 18.7921 | 172.22 | 9300 | 265.1793 | 0.3024 | |
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| 16.5106 | 177.77 | 9600 | 269.0261 | 0.2977 | |
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| 17.1239 | 183.33 | 9900 | 261.8192 | 0.2956 | |
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| 15.4832 | 188.88 | 10200 | 271.2451 | 0.2982 | |
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| 16.2146 | 194.44 | 10500 | 269.5397 | 0.2957 | |
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| 13.7332 | 199.99 | 10800 | 276.0069 | 0.3017 | |
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| 13.914 | 205.55 | 11100 | 278.2491 | 0.3023 | |
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| 13.7551 | 211.11 | 11400 | 260.8341 | 0.2900 | |
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| 11.6575 | 216.66 | 11700 | 276.8361 | 0.2906 | |
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| 12.4438 | 222.22 | 12000 | 280.0102 | 0.2954 | |
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| 13.1577 | 227.77 | 12300 | 268.7986 | 0.2949 | |
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| 12.2083 | 233.33 | 12600 | 272.5989 | 0.2949 | |
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| 11.1147 | 238.88 | 12900 | 287.3684 | 0.2978 | |
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### Framework versions |
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- Transformers 4.16.2 |
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- Pytorch 1.8.1+cu101 |
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- Datasets 1.18.3 |
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- Tokenizers 0.11.0 |
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