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--- |
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license: apache-2.0 |
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tags: |
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- automatic-speech-recognition |
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- mozilla-foundation/common_voice_8_0 |
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- generated_from_trainer |
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- dv |
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- robust-speech-event |
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- model_for_talk |
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datasets: |
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- mozilla-foundation/common_voice_8_0 |
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model-index: |
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- name: wav2vec2-xls-r-1b-dv |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: Common Voice 8 |
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type: mozilla-foundation/common_voice_8_0 |
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args: dv |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 21.32 |
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- name: Test CER |
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type: cer |
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value: 3.43 |
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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-1b-dv |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the common_voice dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1702 |
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- Wer: 0.2123 |
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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: 4.5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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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: 30 |
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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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| 3.8412 | 0.66 | 400 | 0.7160 | 0.7913 | |
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| 0.6832 | 1.33 | 800 | 0.3401 | 0.5268 | |
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| 0.4624 | 1.99 | 1200 | 0.2671 | 0.4683 | |
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| 0.3832 | 2.65 | 1600 | 0.2395 | 0.4410 | |
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| 0.3443 | 3.32 | 2000 | 0.2410 | 0.4296 | |
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| 0.324 | 3.98 | 2400 | 0.2302 | 0.4143 | |
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| 0.2934 | 4.64 | 2800 | 0.2402 | 0.4136 | |
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| 0.2773 | 5.31 | 3200 | 0.2134 | 0.4088 | |
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| 0.2638 | 5.97 | 3600 | 0.2072 | 0.4037 | |
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| 0.2479 | 6.63 | 4000 | 0.2036 | 0.3876 | |
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| 0.2424 | 7.3 | 4400 | 0.2037 | 0.3767 | |
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| 0.2249 | 7.96 | 4800 | 0.1959 | 0.3802 | |
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| 0.2169 | 8.62 | 5200 | 0.1943 | 0.3813 | |
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| 0.2109 | 9.29 | 5600 | 0.1944 | 0.3691 | |
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| 0.1991 | 9.95 | 6000 | 0.1870 | 0.3589 | |
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| 0.1917 | 10.61 | 6400 | 0.1834 | 0.3485 | |
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| 0.1862 | 11.28 | 6800 | 0.1857 | 0.3486 | |
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| 0.1744 | 11.94 | 7200 | 0.1812 | 0.3330 | |
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| 0.171 | 12.6 | 7600 | 0.1797 | 0.3436 | |
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| 0.1599 | 13.27 | 8000 | 0.1839 | 0.3319 | |
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| 0.1597 | 13.93 | 8400 | 0.1737 | 0.3385 | |
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| 0.1494 | 14.59 | 8800 | 0.1807 | 0.3239 | |
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| 0.1444 | 15.26 | 9200 | 0.1750 | 0.3155 | |
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| 0.1382 | 15.92 | 9600 | 0.1705 | 0.3084 | |
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| 0.1299 | 16.58 | 10000 | 0.1777 | 0.2999 | |
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| 0.1306 | 17.25 | 10400 | 0.1765 | 0.3056 | |
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| 0.1239 | 17.91 | 10800 | 0.1676 | 0.2864 | |
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| 0.1149 | 18.57 | 11200 | 0.1774 | 0.2861 | |
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| 0.1134 | 19.24 | 11600 | 0.1654 | 0.2699 | |
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| 0.1101 | 19.9 | 12000 | 0.1621 | 0.2651 | |
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| 0.1038 | 20.56 | 12400 | 0.1686 | 0.2610 | |
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| 0.1038 | 21.23 | 12800 | 0.1722 | 0.2559 | |
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| 0.0988 | 21.89 | 13200 | 0.1708 | 0.2486 | |
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| 0.0949 | 22.55 | 13600 | 0.1696 | 0.2453 | |
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| 0.0913 | 23.22 | 14000 | 0.1677 | 0.2424 | |
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| 0.0879 | 23.88 | 14400 | 0.1640 | 0.2359 | |
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| 0.0888 | 24.54 | 14800 | 0.1697 | 0.2347 | |
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| 0.0826 | 25.21 | 15200 | 0.1709 | 0.2314 | |
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| 0.0819 | 25.87 | 15600 | 0.1679 | 0.2256 | |
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| 0.0793 | 26.53 | 16000 | 0.1701 | 0.2214 | |
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| 0.0773 | 27.2 | 16400 | 0.1682 | 0.2176 | |
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| 0.0783 | 27.86 | 16800 | 0.1685 | 0.2165 | |
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| 0.074 | 28.52 | 17200 | 0.1688 | 0.2155 | |
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| 0.0753 | 29.19 | 17600 | 0.1695 | 0.2110 | |
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| 0.0699 | 29.85 | 18000 | 0.1702 | 0.2123 | |
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### Framework versions |
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- Transformers 4.17.0.dev0 |
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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 |
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