--- language: - zh-CN license: apache-2.0 tags: - automatic-speech-recognition - common_voice - generated_from_trainer - hf-asr-leaderboard - robust-speech-event - zh datasets: - common_voice model-index: - name: wav2vec2-xls-r-300m-zh-CN results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 7 type: mozilla-foundation/common_voice_7_0 args: zh-CN metrics: - name: Test WER type: wer value: 80 - name: Test CER type: cer value: 40.11 - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Robust Speech Event - Dev Data type: speech-recognition-community-v2/dev_data args: zh-CN metrics: - name: Test CER type: cer value: 69.1 - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Robust Speech Event - Test Data type: speech-recognition-community-v2/eval_data args: zh-CN metrics: - name: Test CER type: cer value: 43.08 --- # wav2vec2-xls-r-300m-zh-CN 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 - ZH-CN dataset. It achieves the following results on the evaluation set: - Loss: 0.8828 - Wer: 2.0604 ## 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: 7.5e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 2000 - num_epochs: 50.0 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:-----:|:---------------:|:------:| | 60.2112 | 0.74 | 500 | 64.8189 | 1.0 | | 8.1128 | 1.48 | 1000 | 6.8997 | 1.0 | | 6.0492 | 2.22 | 1500 | 5.9677 | 1.9495 | | 5.9326 | 2.95 | 2000 | 5.8845 | 1.4092 | | 5.8763 | 3.69 | 2500 | 5.8460 | 1.6126 | | 5.7888 | 4.43 | 3000 | 5.7545 | 2.2034 | | 5.735 | 5.17 | 3500 | 5.6777 | 2.3350 | | 5.6861 | 5.91 | 4000 | 5.5179 | 2.2232 | | 5.381 | 6.65 | 4500 | 5.1420 | 2.1816 | | 4.625 | 7.39 | 5000 | 3.9020 | 2.0722 | | 4.214 | 8.12 | 5500 | 3.3394 | 2.1430 | | 3.8992 | 8.86 | 6000 | 2.9085 | 2.1534 | | 3.6481 | 9.6 | 6500 | 2.6208 | 2.3538 | | 3.4658 | 10.34 | 7000 | 2.3172 | 2.2271 | | 3.257 | 11.08 | 7500 | 2.0916 | 2.1351 | | 3.1294 | 11.82 | 8000 | 1.8954 | 2.2133 | | 3.0266 | 12.56 | 8500 | 1.7673 | 2.0896 | | 2.9451 | 13.29 | 9000 | 1.6659 | 2.1381 | | 2.8802 | 14.03 | 9500 | 1.5637 | 2.1969 | | 2.78 | 14.77 | 10000 | 1.4921 | 2.2335 | | 2.7049 | 15.51 | 10500 | 1.4132 | 2.2217 | | 2.6768 | 16.25 | 11000 | 1.3667 | 2.2232 | | 2.6358 | 16.99 | 11500 | 1.3111 | 2.1286 | | 2.5802 | 17.72 | 12000 | 1.2679 | 2.1430 | | 2.5012 | 18.46 | 12500 | 1.2365 | 2.1153 | | 2.458 | 19.2 | 13000 | 1.2118 | 2.1573 | | 2.4433 | 19.94 | 13500 | 1.1992 | 2.1336 | | 2.438 | 20.68 | 14000 | 1.1803 | 2.1509 | | 2.418 | 21.42 | 14500 | 1.1601 | 2.1232 | | 2.3322 | 22.16 | 15000 | 1.1418 | 2.1930 | | 2.3387 | 22.89 | 15500 | 1.1172 | 2.2464 | | 2.3349 | 23.63 | 16000 | 1.1144 | 2.1856 | | 2.291 | 24.37 | 16500 | 1.1018 | 2.1930 | | 2.2766 | 25.11 | 17000 | 1.0883 | 2.1762 | | 2.2534 | 25.85 | 17500 | 1.0744 | 2.1875 | | 2.2393 | 26.59 | 18000 | 1.0561 | 2.1846 | | 2.2085 | 27.33 | 18500 | 1.0466 | 2.1445 | | 2.1966 | 28.06 | 19000 | 1.0382 | 2.1089 | | 2.1794 | 28.8 | 19500 | 1.0264 | 1.9861 | | 2.1423 | 29.54 | 20000 | 1.0246 | 1.9678 | | 2.1649 | 30.28 | 20500 | 0.9982 | 2.0005 | | 2.143 | 31.02 | 21000 | 0.9985 | 2.0450 | | 2.1338 | 31.76 | 21500 | 0.9932 | 2.0025 | | 2.1076 | 32.5 | 22000 | 0.9903 | 2.0505 | | 2.0519 | 33.23 | 22500 | 0.9834 | 2.0737 | | 2.0534 | 33.97 | 23000 | 0.9756 | 2.0247 | | 2.0121 | 34.71 | 23500 | 0.9688 | 2.1440 | | 2.0161 | 35.45 | 24000 | 0.9582 | 2.1232 | | 2.0178 | 36.19 | 24500 | 0.9480 | 2.0896 | | 2.0154 | 36.93 | 25000 | 0.9483 | 2.0787 | | 1.9966 | 37.67 | 25500 | 0.9406 | 2.0297 | | 1.9753 | 38.4 | 26000 | 0.9419 | 2.0346 | | 1.9524 | 39.14 | 26500 | 0.9274 | 2.0698 | | 1.9427 | 39.88 | 27000 | 0.9233 | 2.0787 | | 1.9258 | 40.62 | 27500 | 0.9182 | 2.0529 | | 1.9031 | 41.36 | 28000 | 0.9150 | 2.0787 | | 1.9297 | 42.1 | 28500 | 0.9040 | 2.0505 | | 1.9041 | 42.84 | 29000 | 0.9009 | 2.0579 | | 1.8929 | 43.57 | 29500 | 0.8968 | 2.0327 | | 1.9077 | 44.31 | 30000 | 0.8954 | 2.0619 | | 1.8504 | 45.05 | 30500 | 0.8922 | 2.0737 | | 1.8732 | 45.79 | 31000 | 0.8898 | 2.0683 | | 1.877 | 46.53 | 31500 | 0.8849 | 2.0589 | | 1.8587 | 47.27 | 32000 | 0.8843 | 2.0450 | | 1.8236 | 48.01 | 32500 | 0.8810 | 2.0554 | | 1.8392 | 48.74 | 33000 | 0.8820 | 2.0574 | | 1.8428 | 49.48 | 33500 | 0.8816 | 2.0668 | ### Framework versions - Transformers 4.17.0.dev0 - Pytorch 1.10.2+cu102 - Datasets 1.18.2.dev0 - Tokenizers 0.11.0 #### Evaluation Commands 1. To evaluate on `mozilla-foundation/common_voice_7_0` with split `test` ```bash python eval.py --model_id samitizerxu/wav2vec2-xls-r-300m-zh-CN --dataset mozilla-foundation/common_voice_7_0 --config zh-CN --split test ``` 2. To evaluate on `speech-recognition-community-v2/dev_data` ```bash python eval.py --model_id samitizerxu/wav2vec2-xls-r-300m-zh-CN --dataset speech-recognition-community-v2/dev_data --config zh-CN --split validation --chunk_length_s 5.0 --stride_length_s 1.0 ```