--- library_name: transformers license: apache-2.0 base_model: openai/whisper-medium tags: - generated_from_trainer datasets: - bigcgen metrics: - wer model-index: - name: whisper-medium-bigcgen-combined-20hrs-model results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: bigcgen type: bigcgen metrics: - name: Wer type: wer value: 0.4210649229332088 --- # whisper-medium-bigcgen-combined-20hrs-model This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co./openai/whisper-medium) on the bigcgen dataset. It achieves the following results on the evaluation set: - Loss: 0.5368 - Wer: 0.4211 ## 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: 1.75e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - 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: 5000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:------:|:----:|:---------------:|:------:| | 3.7679 | 0.1521 | 200 | 0.8942 | 0.6455 | | 3.4733 | 0.3042 | 400 | 0.7609 | 0.5650 | | 2.6698 | 0.4564 | 600 | 0.6958 | 0.5375 | | 2.5647 | 0.6085 | 800 | 0.6685 | 0.5496 | | 2.1636 | 0.7606 | 1000 | 0.6228 | 0.5103 | | 2.7265 | 0.9127 | 1200 | 0.5869 | 0.4706 | | 1.5404 | 1.0654 | 1400 | 0.5990 | 0.4542 | | 1.9844 | 1.2175 | 1600 | 0.5893 | 0.4643 | | 1.6926 | 1.3697 | 1800 | 0.5730 | 0.4413 | | 1.8654 | 1.5218 | 2000 | 0.5550 | 0.4599 | | 1.8045 | 1.6739 | 2200 | 0.5445 | 0.4178 | | 1.8258 | 1.8260 | 2400 | 0.5368 | 0.4211 | | 1.543 | 1.9781 | 2600 | 0.5371 | 0.4245 | | 0.9667 | 2.1308 | 2800 | 0.5587 | 0.4545 | | 1.0216 | 2.2829 | 3000 | 0.5617 | 0.4096 | ### Framework versions - Transformers 4.47.1 - Pytorch 2.5.1+cu124 - Datasets 3.2.0 - Tokenizers 0.21.0