--- library_name: transformers language: - en license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_trainer datasets: - wwwtwwwt/fineaudio-Entertainment metrics: - wer model-index: - name: Whisper Tiny En - Entertainment - Game Commentary results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: fineaudio-Entertainment-Game Commentary type: wwwtwwwt/fineaudio-Entertainment args: 'config: en, split: test' metrics: - name: Wer type: wer value: 46.31946283631152 --- # Whisper Tiny En - Entertainment - Game Commentary This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the fineaudio-Entertainment-Game Commentary dataset. It achieves the following results on the evaluation set: - Loss: 0.8817 - Wer: 46.3195 ## 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: 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: 500 - training_steps: 4000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:------:|:----:|:---------------:|:-------:| | 0.8341 | 0.5984 | 1000 | 0.9697 | 53.8799 | | 0.6267 | 1.1969 | 2000 | 0.9055 | 49.3543 | | 0.6058 | 1.7953 | 3000 | 0.8844 | 47.1311 | | 0.5022 | 2.3938 | 4000 | 0.8817 | 46.3195 | ### Framework versions - Transformers 4.46.3 - Pytorch 2.4.0 - Datasets 3.1.0 - Tokenizers 0.20.0