--- library_name: transformers language: - fa license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_trainer datasets: - mozilla-foundation/common_voice_17_0 metrics: - wer model-index: - name: 'Whisper tiny Fa ' results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 17.0 type: mozilla-foundation/common_voice_17_0 config: fa split: None args: 'config: fa, split: test' metrics: - name: Wer type: wer value: 51.8555393407073 --- # Whisper tiny Fa This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set: - Loss: 0.5542 - Wer: 51.8555 ## 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: 2e-05 - train_batch_size: 32 - 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: 1000 - training_steps: 5000 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:------:|:----:|:---------------:|:-------:| | 0.5002 | 0.8110 | 1000 | 0.7493 | 67.9014 | | 0.3239 | 1.6221 | 2000 | 0.6166 | 58.6680 | | 0.2198 | 2.4331 | 3000 | 0.5782 | 54.3310 | | 0.1695 | 3.2441 | 4000 | 0.5619 | 52.7925 | | 0.1309 | 4.0552 | 5000 | 0.5542 | 51.8555 | ### Framework versions - Transformers 4.44.2 - Pytorch 2.3.1+cu121 - Datasets 2.21.0 - Tokenizers 0.19.1