--- language: - en license: apache-2.0 base_model: openai/whisper-tiny.en tags: - nyansapo_ai-asr-leaderboard - generated_from_trainer datasets: - NyansapoAI/azure-dataset metrics: - wer model-index: - name: whisper-tiny.en results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Azure-dataset type: NyansapoAI/azure-dataset args: 'split: test' metrics: - name: Wer type: wer value: 44.34857635893012 --- # whisper-tiny.en This model is a fine-tuned version of [openai/whisper-tiny.en](https://huggingface.co/openai/whisper-tiny.en) on the Azure-dataset dataset. It achieves the following results on the evaluation set: - Loss: 0.0680 - Wer: 44.3486 ## 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: 250 - training_steps: 1000 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 1.2415 | 1.38 | 250 | 0.6131 | 26.6609 | | 0.3582 | 2.76 | 500 | 0.0882 | 43.0544 | | 0.2094 | 4.14 | 750 | 0.0723 | 43.6583 | | 0.1788 | 5.52 | 1000 | 0.0680 | 44.3486 | ### Framework versions - Transformers 4.39.1 - Pytorch 2.2.1 - Datasets 2.18.0 - Tokenizers 0.15.2