--- language: - en license: apache-2.0 base_model: openai/whisper-small tags: - generated_from_trainer datasets: - mShiry/ATC_combined metrics: - wer model-index: - name: Whisper Small ATC - ATCText results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: ATC type: mShiry/ATC_combined args: 'split: test' metrics: - name: Wer type: wer value: 10.612930650580948 --- # Whisper Small ATC - ATCText This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the ATC dataset. It achieves the following results on the evaluation set: - Loss: 0.2486 - Wer: 10.6129 ## 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: 8 - 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: 4000 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.2533 | 0.42 | 1000 | 0.3465 | 16.2868 | | 0.235 | 0.84 | 2000 | 0.2881 | 13.5237 | | 0.0851 | 1.27 | 3000 | 0.2607 | 10.6048 | | 0.1317 | 1.69 | 4000 | 0.2486 | 10.6129 | ### Framework versions - Transformers 4.39.3 - Pytorch 2.2.2 - Datasets 2.18.0 - Tokenizers 0.15.2