--- license: apache-2.0 tags: - whisper-event - generated_from_trainer datasets: - google/fleurs metrics: - wer model-index: - name: Whisper Medium Pashto results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: google/fleurs ps_af type: google/fleurs config: ps_af split: test args: ps_af metrics: - name: Wer type: wer value: 50.6431598062954 --- # Whisper Medium Pashto This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co./openai/whisper-medium) on the google/fleurs ps_af dataset. It achieves the following results on the evaluation set: - Loss: 1.2950 - Wer: 50.6432 ## 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: 32 - eval_batch_size: 16 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 64 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 50 - training_steps: 500 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.0139 | 14.29 | 100 | 1.0302 | 50.1211 | | 0.0011 | 28.57 | 200 | 1.2129 | 49.7806 | | 0.0008 | 42.86 | 300 | 1.2581 | 50.3178 | | 0.0007 | 57.14 | 400 | 1.2850 | 50.5524 | | 0.0007 | 71.43 | 500 | 1.2950 | 50.6432 | ### Framework versions - Transformers 4.26.0.dev0 - Pytorch 1.13.0+cu117 - Datasets 2.7.1.dev0 - Tokenizers 0.13.2