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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-large-xlsr-53 |
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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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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-large-xlsr53-zh-cn-subset20-colab |
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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 |
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type: common_voice |
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config: zh-CN |
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split: test[:20%] |
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args: zh-CN |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.9503424657534246 |
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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-large-xlsr53-zh-cn-subset20-colab |
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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 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.0566 |
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- Wer: 0.9503 |
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- Cer: 0.3333 |
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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: 0.0003 |
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- train_batch_size: 13 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 26 |
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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: 100 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:| |
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| No log | 1.9 | 400 | 6.7551 | 1.0 | 1.0 | |
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| 34.7845 | 3.81 | 800 | 6.4563 | 1.0 | 1.0 | |
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| 6.4358 | 5.71 | 1200 | 4.2319 | 1.0074 | 0.7454 | |
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| 4.2052 | 7.62 | 1600 | 2.6538 | 1.0200 | 0.5562 | |
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| 2.3906 | 9.52 | 2000 | 2.3565 | 1.0063 | 0.5147 | |
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| 2.3906 | 11.43 | 2400 | 2.1287 | 0.9863 | 0.4822 | |
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| 1.93 | 13.33 | 2800 | 1.9585 | 0.9812 | 0.4528 | |
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| 1.6322 | 15.24 | 3200 | 1.8771 | 0.9937 | 0.4381 | |
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| 1.3629 | 17.14 | 3600 | 1.8405 | 0.9926 | 0.4242 | |
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| 1.166 | 19.05 | 4000 | 1.7674 | 0.9989 | 0.4140 | |
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| 1.166 | 20.95 | 4400 | 1.7879 | 0.9795 | 0.4047 | |
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| 0.9915 | 22.86 | 4800 | 1.7597 | 1.0126 | 0.4080 | |
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| 0.8517 | 24.76 | 5200 | 1.7726 | 0.9829 | 0.3966 | |
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| 0.7143 | 26.67 | 5600 | 1.7623 | 0.9732 | 0.3863 | |
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| 0.6267 | 28.57 | 6000 | 1.8164 | 0.9720 | 0.3863 | |
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| 0.6267 | 30.48 | 6400 | 1.8136 | 0.9680 | 0.3801 | |
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| 0.5389 | 32.38 | 6800 | 1.8696 | 0.9652 | 0.3812 | |
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| 0.4764 | 34.29 | 7200 | 1.8625 | 0.9663 | 0.3744 | |
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| 0.4095 | 36.19 | 7600 | 1.8868 | 0.9618 | 0.3683 | |
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| 0.3594 | 38.1 | 8000 | 1.8834 | 0.9623 | 0.3699 | |
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| 0.3594 | 40.0 | 8400 | 1.9155 | 0.9589 | 0.3670 | |
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| 0.3064 | 41.9 | 8800 | 1.9268 | 0.9652 | 0.3688 | |
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| 0.2825 | 43.81 | 9200 | 1.9527 | 0.9697 | 0.3674 | |
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| 0.2524 | 45.71 | 9600 | 1.9726 | 0.9686 | 0.3617 | |
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| 0.2272 | 47.62 | 10000 | 1.9594 | 0.9629 | 0.3619 | |
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| 0.2272 | 49.52 | 10400 | 1.9799 | 0.9635 | 0.3607 | |
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| 0.2042 | 51.43 | 10800 | 2.0175 | 0.9669 | 0.3582 | |
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| 0.1975 | 53.33 | 11200 | 2.0246 | 0.9589 | 0.3571 | |
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| 0.1827 | 55.24 | 11600 | 2.0535 | 0.9703 | 0.3600 | |
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| 0.1677 | 57.14 | 12000 | 2.0458 | 0.9583 | 0.3555 | |
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| 0.1677 | 59.05 | 12400 | 2.0893 | 0.9572 | 0.3583 | |
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| 0.1626 | 60.95 | 12800 | 2.0729 | 0.9600 | 0.3557 | |
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| 0.155 | 62.86 | 13200 | 2.0706 | 0.9572 | 0.3538 | |
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| 0.1456 | 64.76 | 13600 | 2.0761 | 0.9532 | 0.3553 | |
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| 0.1337 | 66.67 | 14000 | 2.0349 | 0.9589 | 0.3474 | |
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| 0.1337 | 68.57 | 14400 | 2.0844 | 0.9549 | 0.3484 | |
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| 0.1274 | 70.48 | 14800 | 2.0874 | 0.9578 | 0.3505 | |
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| 0.1198 | 72.38 | 15200 | 2.0813 | 0.9526 | 0.3473 | |
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| 0.1164 | 74.29 | 15600 | 2.0866 | 0.9498 | 0.3473 | |
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| 0.1105 | 76.19 | 16000 | 2.0688 | 0.9486 | 0.3421 | |
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| 0.1105 | 78.1 | 16400 | 2.0854 | 0.9498 | 0.3431 | |
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| 0.1053 | 80.0 | 16800 | 2.0749 | 0.9503 | 0.3414 | |
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| 0.1 | 81.9 | 17200 | 2.0622 | 0.9543 | 0.3407 | |
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| 0.0977 | 83.81 | 17600 | 2.0678 | 0.9532 | 0.3396 | |
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| 0.0906 | 85.71 | 18000 | 2.0650 | 0.9515 | 0.3383 | |
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| 0.0906 | 87.62 | 18400 | 2.0631 | 0.9492 | 0.3378 | |
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| 0.0867 | 89.52 | 18800 | 2.0633 | 0.9521 | 0.3365 | |
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| 0.0836 | 91.43 | 19200 | 2.0606 | 0.9532 | 0.3346 | |
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| 0.0819 | 93.33 | 19600 | 2.0671 | 0.9538 | 0.3355 | |
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| 0.0768 | 95.24 | 20000 | 2.0661 | 0.9509 | 0.3338 | |
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| 0.0768 | 97.14 | 20400 | 2.0564 | 0.9498 | 0.3335 | |
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| 0.0752 | 99.05 | 20800 | 2.0566 | 0.9503 | 0.3333 | |
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### Framework versions |
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- Transformers 4.32.0.dev0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.3 |
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- Tokenizers 0.13.3 |
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