--- language: - zh license: apache-2.0 tags: - hf-asr-leaderboard - generated_from_trainer datasets: - mozilla-foundation/common_voice_11_0 metrics: - wer model-index: - name: Whisper Tiny Zh - Sanchit Gandhi results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 11.0 type: mozilla-foundation/common_voice_11_0 config: zh-CN split: test args: 'config: zh, split: test' metrics: - name: Wer type: wer value: 111.34001134001134 --- # Whisper Tiny Zh - Sanchit Gandhi This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set: - Loss: 0.5909 - Wer: 111.3400 ## 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: 1e-05 - train_batch_size: 16 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - training_steps: 4000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.7098 | 0.4 | 1000 | 0.6905 | 106.4733 | | 0.7108 | 0.81 | 2000 | 0.6273 | 106.5394 | | 0.6124 | 1.21 | 3000 | 0.6009 | 112.0582 | | 0.5633 | 1.61 | 4000 | 0.5909 | 111.3400 | ### Framework versions - Transformers 4.28.1 - Pytorch 2.0.0+cu117 - Datasets 2.12.0 - Tokenizers 0.13.3