--- tags: - generated_from_trainer datasets: - common_voice metrics: - wer model-index: - name: wavlm-base-plus_zh_tw_ver2 results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: common_voice type: common_voice config: zh-TW split: test args: zh-TW metrics: - name: Wer type: wer value: 1.0 --- # wavlm-base-plus_zh_tw_ver2 This model is a fine-tuned version of [microsoft/wavlm-base-plus](https://huggingface.co/microsoft/wavlm-base-plus) on the common_voice dataset. It achieves the following results on the evaluation set: - Loss: 6.5278 - Wer: 1.0 ## 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: 32 - eval_batch_size: 2 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 2000 - num_epochs: 100.0 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:-----:|:---------------:|:---:| | 82.628 | 2.5 | 500 | 79.5587 | 1.0 | | 17.5635 | 5.0 | 1000 | 11.5929 | 1.0 | | 6.4288 | 7.5 | 1500 | 6.4475 | 1.0 | | 6.4092 | 10.0 | 2000 | 6.4579 | 1.0 | | 6.3982 | 12.5 | 2500 | 6.4662 | 1.0 | | 6.391 | 15.0 | 3000 | 6.4655 | 1.0 | | 6.4097 | 17.5 | 3500 | 6.4691 | 1.0 | | 6.3986 | 20.0 | 4000 | 6.4702 | 1.0 | | 6.4069 | 22.5 | 4500 | 6.4761 | 1.0 | | 6.4158 | 25.0 | 5000 | 6.4750 | 1.0 | | 6.4117 | 27.5 | 5500 | 6.4816 | 1.0 | | 6.4086 | 30.0 | 6000 | 6.4806 | 1.0 | | 6.3992 | 32.5 | 6500 | 6.4872 | 1.0 | | 6.3946 | 35.0 | 7000 | 6.4866 | 1.0 | | 6.4212 | 37.5 | 7500 | 6.4895 | 1.0 | | 6.4051 | 40.0 | 8000 | 6.4926 | 1.0 | | 6.398 | 42.5 | 8500 | 6.5015 | 1.0 | | 6.3967 | 45.0 | 9000 | 6.4960 | 1.0 | | 6.4096 | 47.5 | 9500 | 6.5003 | 1.0 | | 6.4068 | 50.0 | 10000 | 6.5026 | 1.0 | | 6.4062 | 52.5 | 10500 | 6.5071 | 1.0 | | 6.395 | 55.0 | 11000 | 6.5066 | 1.0 | | 6.4079 | 57.5 | 11500 | 6.5093 | 1.0 | | 6.411 | 60.0 | 12000 | 6.5106 | 1.0 | | 6.4023 | 62.5 | 12500 | 6.5112 | 1.0 | | 6.4053 | 65.0 | 13000 | 6.5143 | 1.0 | | 6.4103 | 67.5 | 13500 | 6.5172 | 1.0 | | 6.3899 | 70.0 | 14000 | 6.5182 | 1.0 | | 6.4054 | 72.5 | 14500 | 6.5197 | 1.0 | | 6.391 | 75.0 | 15000 | 6.5200 | 1.0 | | 6.3988 | 77.5 | 15500 | 6.5220 | 1.0 | | 6.4059 | 80.0 | 16000 | 6.5228 | 1.0 | | 6.392 | 82.5 | 16500 | 6.5233 | 1.0 | | 6.3947 | 85.0 | 17000 | 6.5253 | 1.0 | | 6.3966 | 87.5 | 17500 | 6.5259 | 1.0 | | 6.3905 | 90.0 | 18000 | 6.5264 | 1.0 | | 6.4003 | 92.5 | 18500 | 6.5272 | 1.0 | | 6.3877 | 95.0 | 19000 | 6.5275 | 1.0 | | 6.3903 | 97.5 | 19500 | 6.5277 | 1.0 | | 6.3944 | 100.0 | 20000 | 6.5278 | 1.0 | ### Framework versions - Transformers 4.28.0.dev0 - Pytorch 1.12.0+cu102 - Datasets 2.10.1 - Tokenizers 0.13.2