--- license: apache-2.0 tags: - generated_from_trainer datasets: - common_voice_11_0 metrics: - wer model-index: - name: output_dir results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: common_voice_11_0 type: common_voice_11_0 config: rw split: test args: rw metrics: - name: Wer type: wer value: 43.75236083594792 --- # output_dir This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the common_voice_11_0 dataset. It achieves the following results on the evaluation set: - Loss: 0.6424 - Wer: 43.7524 ## 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: 20 - eval_batch_size: 20 - seed: 42 - distributed_type: multi-GPU - num_devices: 2 - total_train_batch_size: 40 - total_eval_batch_size: 40 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - training_steps: 5000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.7471 | 0.04 | 1000 | 0.9044 | 59.2903 | | 0.5987 | 0.08 | 2000 | 0.7523 | 52.0232 | | 0.5168 | 0.12 | 3000 | 0.6890 | 47.7610 | | 0.5082 | 0.16 | 4000 | 0.6596 | 45.4013 | | 0.4748 | 0.2 | 5000 | 0.6424 | 43.7524 | ### Framework versions - Transformers 4.26.0.dev0 - Pytorch 1.13.1+cu116 - Datasets 2.7.1.dev0 - Tokenizers 0.13.2