--- license: apache-2.0 tags: - generated_from_trainer datasets: - mozilla-foundation/common_voice_11_0 metrics: - wer model-index: - name: whisper-small-hi results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: mozilla-foundation/common_voice_11_0 hi type: mozilla-foundation/common_voice_11_0 config: hi split: None args: hi metrics: - name: Wer type: wer value: 0.330906628290866 --- # whisper-small-hi This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0 hi dataset. It achieves the following results on the evaluation set: - Loss: 0.5355 - Wer: 0.3309 ## 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: 16 - seed: 42 - gradient_accumulation_steps: 2 - 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: 500 - training_steps: 5000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:------:| | 0.0534 | 4.89 | 1000 | 0.3375 | 0.3465 | | 0.0042 | 9.78 | 2000 | 0.4443 | 0.3402 | | 0.0002 | 14.67 | 3000 | 0.4973 | 0.3301 | | 0.0001 | 19.56 | 4000 | 0.5254 | 0.3309 | | 0.0001 | 24.45 | 5000 | 0.5355 | 0.3309 | ### Framework versions - Transformers 4.28.0.dev0 - Pytorch 2.0.0+cu117 - Datasets 2.11.0 - Tokenizers 0.13.3