--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_trainer datasets: - audiofolder metrics: - wer model-index: - name: whisper-tiny-300v2 results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: audiofolder type: audiofolder config: default split: test args: default metrics: - name: Wer type: wer value: 86.48648648648648 --- # whisper-tiny-300v2 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the audiofolder dataset. It achieves the following results on the evaluation set: - Loss: 1.4117 - Wer Ortho: 83.7838 - Wer: 86.4865 ## 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: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: constant_with_warmup - lr_scheduler_warmup_steps: 30 - training_steps: 300 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer | |:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:| | 0.2322 | 20.0 | 60 | 1.3194 | 83.7838 | 83.7838 | | 0.0267 | 40.0 | 120 | 1.3785 | 81.0811 | 81.0811 | | 0.0002 | 60.0 | 180 | 1.3838 | 81.0811 | 81.0811 | | 0.0001 | 80.0 | 240 | 1.4049 | 83.7838 | 83.7838 | | 0.0 | 100.0 | 300 | 1.4117 | 83.7838 | 86.4865 | ### Framework versions - Transformers 4.41.2 - Pytorch 2.3.0+cu121 - Datasets 2.19.1 - Tokenizers 0.19.1