--- license: apache-2.0 base_model: openai/whisper-small tags: - generated_from_trainer datasets: - mozilla-foundation/common_voice_9_0 metrics: - wer model-index: - name: yt-special-batch88 results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: mozilla-foundation/common_voice_9_0 id type: mozilla-foundation/common_voice_9_0 config: id split: train args: id metrics: - name: Wer type: wer value: 5.357219480798112 --- # yt-special-batch88 This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_9_0 id dataset. It achieves the following results on the evaluation set: - Loss: 0.2602 - Wer: 5.3572 ## 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: 8 - 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: 5000 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 37.1656 | 1.58 | 1000 | 31.4152 | 569.1440 | | 15.0344 | 3.17 | 2000 | 13.2072 | 144.3489 | | 7.6075 | 4.75 | 3000 | 5.8946 | 42.3836 | | 2.5225 | 6.34 | 4000 | 2.0158 | 19.5430 | | 0.5364 | 7.92 | 5000 | 0.2602 | 5.3572 | ### Framework versions - Transformers 4.31.0.dev0 - Pytorch 2.0.1+cu117 - Datasets 2.13.1 - Tokenizers 0.13.3