--- language: - fa license: apache-2.0 tags: - whisper-event - generated_from_trainer datasets: - mozilla-foundation/common_voice_11_0 metrics: - wer model-index: - name: Whisper_large_Persian results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: mozilla-foundation/common_voice_11_0 fa type: mozilla-foundation/common_voice_11_0 config: fa split: test metrics: - name: Wer type: wer value: 26.367876079171644 --- # Whisper large persian This model is a fine-tuned version of [anuragshas/whisper-large-v2-hi](https://huggingface.co/anuragshas/whisper-large-v2-hi) on the mozilla-foundation/common_voice_11_0 fa dataset. It achieves the following results on the evaluation set: - Loss: 0.3047 - Wer: 26.3679 ## 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: 8 - eval_batch_size: 16 - seed: 42 - distributed_type: multi-GPU - gradient_accumulation_steps: 2 - total_train_batch_size: 16 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 100 - training_steps: 1000 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.2948 | 0.19 | 250 | 0.4258 | 35.6023 | | 0.2443 | 0.39 | 500 | 0.3650 | 30.9747 | | 0.1956 | 0.58 | 750 | 0.3228 | 28.0196 | | 0.1715 | 0.78 | 1000 | 0.3047 | 26.3679 | ### Framework versions - Transformers 4.25.1 - Pytorch 1.13.1+cu117 - Datasets 2.8.0 - Tokenizers 0.13.2