--- tags: - generated_from_trainer datasets: - afrispeech-200 metrics: - wer model-index: - name: afripspeech_data_aug results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: afrispeech-200 type: afrispeech-200 config: all split: train args: all metrics: - name: Wer type: wer value: 6.008 --- # afripspeech_data_aug This model is a fine-tuned version of [afrispeech_large_A100](https://huggingface.co/Seyfelislem/afrispeech_large_A100) on the afrispeech-200 dataset. ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 1e-05 - train_batch_size: 32 - eval_batch_size: 8 - 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: 500 - training_steps: 2000 - mixed_precision_training: Native AMP ### Training results https://huggingface.co/Seyfelislem/afripspeech_data_aug/tensorboard ### Framework versions - Transformers 4.29.1 - Pytorch 1.13.1 - Datasets 2.12.0 - Tokenizers 0.13.3