--- language: - en license: apache-2.0 base_model: openai/whisper-small.en tags: - nyansapo_ai-asr-leaderboard - generated_from_trainer datasets: - NyansapoAI/azure-dataset metrics: - wer model-index: - name: whisper-small.en results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Azure-dataset type: NyansapoAI/azure-dataset config: default split: test args: 'split: test' metrics: - name: Wer type: wer value: 12.02020202020202 --- # whisper-small.en This model is a fine-tuned version of [openai/whisper-small.en](https://huggingface.co/openai/whisper-small.en) on the Azure-dataset dataset. It achieves the following results on the evaluation set: - Loss: 0.0191 - Wer: 12.0202 ## 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: 2500 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.1119 | 3.11 | 500 | 0.0303 | 27.8788 | | 0.0514 | 6.21 | 1000 | 0.0196 | 16.4646 | | 0.0489 | 9.32 | 1500 | 0.0193 | 9.8990 | | 0.0478 | 12.42 | 2000 | 0.0193 | 11.9192 | | 0.0493 | 15.53 | 2500 | 0.0191 | 12.0202 | ### Framework versions - Transformers 4.33.0.dev0 - Pytorch 2.0.1 - Datasets 2.14.4 - Tokenizers 0.13.3