--- library_name: transformers license: apache-2.0 base_model: openai/whisper-base tags: - generated_from_trainer datasets: - razhan/DOLMA-speech metrics: - wer model-index: - name: whisper-base-zza results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: razhan/DOLMA-speech zazaki type: razhan/DOLMA-speech args: zazaki metrics: - name: Wer type: wer value: 1.2574447646493756 --- # whisper-base-zza This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the razhan/DOLMA-speech zazaki dataset. It achieves the following results on the evaluation set: - Loss: 4.0956 - Wer: 1.2574 - Cer: 1.0132 ## 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: 192 - eval_batch_size: 128 - seed: 42 - distributed_type: multi-GPU - num_devices: 2 - total_train_batch_size: 384 - total_eval_batch_size: 256 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 1 - num_epochs: 5.0 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:| | No log | 1.0 | 1 | 4.7831 | 1.2622 | 1.0146 | | No log | 2.0 | 2 | 4.7831 | 1.2622 | 1.0146 | | No log | 3.0 | 3 | 4.7831 | 1.2622 | 1.0146 | | No log | 4.0 | 4 | 4.7831 | 1.2622 | 1.0146 | | No log | 5.0 | 5 | 4.0956 | 1.2574 | 1.0132 | ### Framework versions - Transformers 4.49.0.dev0 - Pytorch 2.6.0+cu124 - Datasets 3.2.0 - Tokenizers 0.21.0