--- license: apache-2.0 tags: - generated_from_trainer metrics: - wer model-index: - name: Whisper-Small-TF-TIMIT-FLEUR-Normalizado results: [] --- # Whisper-Small-TF-TIMIT-FLEUR-Normalizado This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.7395 - Wer: 85.3796 ## 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: 16 - eval_batch_size: 8 - 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: 3000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.5923 | 1.27 | 500 | 0.9379 | 98.7612 | | 0.1823 | 2.54 | 1000 | 0.6721 | 89.3262 | | 0.0852 | 3.81 | 1500 | 0.6534 | 86.1141 | | 0.0327 | 5.08 | 2000 | 0.6794 | 84.4019 | | 0.0106 | 6.35 | 2500 | 0.7170 | 82.5587 | | 0.0064 | 7.61 | 3000 | 0.7395 | 85.3796 | ### Framework versions - Transformers 4.28.0.dev0 - Pytorch 1.13.0 - Datasets 2.1.0 - Tokenizers 0.13.2