--- language: - fa license: apache-2.0 base_model: openai/whisper-small tags: - hf-asr-leaderboard - generated_from_trainer datasets: - mozilla-foundation/common_voice_16_0 metrics: - wer model-index: - name: Whisper Small Fa - Brett OConnor results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 16.0 type: mozilla-foundation/common_voice_16_0 config: fa split: None args: 'config: fa, split: test' metrics: - name: Wer type: wer value: 36.47368708374277 --- # Whisper Small Fa - Brett OConnor This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 16.0 dataset. It achieves the following results on the evaluation set: - Loss: 0.3430 - Wer: 36.4737 ## 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: 5000 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.2624 | 0.41 | 1000 | 0.4720 | 46.3383 | | 0.2143 | 0.81 | 2000 | 0.4001 | 41.8932 | | 0.1133 | 1.22 | 3000 | 0.3755 | 38.6805 | | 0.1196 | 1.63 | 4000 | 0.3492 | 36.6661 | | 0.0729 | 2.03 | 5000 | 0.3430 | 36.4737 | ### Framework versions - Transformers 4.38.2 - Pytorch 2.2.1+cu121 - Datasets 2.18.0 - Tokenizers 0.15.2