--- language: - hi license: apache-2.0 base_model: openai/whisper-small tags: - hf-asr-leaderboard - generated_from_trainer datasets: - mozilla-foundation/common_voice_13_0 metrics: - wer model-index: - name: Whisper Small Hi - Prox results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 13.0 type: mozilla-foundation/common_voice_13_0 config: hi split: test args: 'config: hi, split: test' metrics: - name: Wer type: wer value: 32.274628348999954 --- # Whisper Small Hi - Prox This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 13.0 dataset. It achieves the following results on the evaluation set: - Loss: 0.4138 - Wer: 32.2746 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.0823 | 2.36 | 1000 | 0.2898 | 34.5522 | | 0.0214 | 4.73 | 2000 | 0.3268 | 33.1567 | | 0.0027 | 7.09 | 3000 | 0.3842 | 32.4196 | | 0.0005 | 9.46 | 4000 | 0.4138 | 32.2746 | ### Framework versions - Transformers 4.40.0.dev0 - Pytorch 2.1.2 - Datasets 2.1.0 - Tokenizers 0.15.2