--- license: apache-2.0 tags: - whisper-event - generated_from_trainer datasets: - google/fleurs metrics: - wer model-index: - name: Whisper Small 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: 56.651029055690074 --- # Whisper Small Pashto This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the google/fleurs ps_af dataset. It achieves the following results on the evaluation set: - Loss: 1.2273 - Wer: 56.6510 ## 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: 3e-07 - train_batch_size: 64 - eval_batch_size: 32 - 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: 800 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:------:|:----:|:---------------:|:-------:| | 2.1183 | 3.7 | 100 | 1.3170 | 76.9522 | | 0.8565 | 7.41 | 200 | 0.9367 | 61.9930 | | 0.2246 | 11.11 | 300 | 0.9642 | 58.8302 | | 0.054 | 14.81 | 400 | 1.0876 | 57.9903 | | 0.0159 | 18.52 | 500 | 1.1798 | 57.8768 | | 0.0045 | 22.22 | 600 | 1.2309 | 56.6510 | | 0.0026 | 100.0 | 700 | 1.2581 | 56.8478 | | 0.0023 | 114.29 | 800 | 1.2710 | 56.7570 | ### Framework versions - Transformers 4.26.0.dev0 - Pytorch 1.13.1+cu117 - Datasets 2.7.1.dev0 - Tokenizers 0.13.2