--- license: apache-2.0 tags: - whisper-event - generated_from_trainer datasets: - google/fleurs metrics: - wer model-index: - name: Whisper_small_Shona results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: google/fleurs type: google/fleurs config: sn_zw split: test metrics: - name: Wer type: wer value: 50.85625 --- # Whisper_small_Shona This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the google/fleurs sn_zw dataset. It achieves the following results on the evaluation set: - Loss: 1.1174 - Wer: 50.8563 ## 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 - num_devices: 4 - gradient_accumulation_steps: 2 - total_train_batch_size: 64 - total_eval_batch_size: 64 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - training_steps: 2000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:------:|:----:|:---------------:|:-------:| | 0.0054 | 33.32 | 400 | 0.9826 | 51.6687 | | 0.0009 | 66.64 | 800 | 1.0774 | 50.9062 | | 0.0005 | 99.96 | 1200 | 1.1174 | 50.8563 | | 0.0003 | 133.32 | 1600 | 1.1388 | 50.875 | | 0.0003 | 166.64 | 2000 | 1.1461 | 50.925 | ### Framework versions - Transformers 4.25.1 - Pytorch 1.13.0+cu117 - Datasets 2.7.1 - Tokenizers 0.13.2