--- language: - en license: apache-2.0 tags: - generated_from_trainer base_model: openai/whisper-tiny datasets: - mozilla-foundation/common_voice_17_0 - google/fleurs - facebook/voxpopuli metrics: - wer model-index: - name: Whisper Medium en results: - task: type: automatic-speech-recognition name: Automatic Speech Recognition dataset: name: Common Voice 17.0 type: mozilla-foundation/common_voice_17_0 config: en split: test args: en metrics: - type: wer value: 26.48273129329958 name: Wer - task: type: automatic-speech-recognition name: Automatic Speech Recognition dataset: name: google/fleurs type: google/fleurs config: en_us split: test metrics: - type: wer value: 14.78 name: WER - task: type: automatic-speech-recognition name: Automatic Speech Recognition dataset: name: facebook/voxpopuli type: facebook/voxpopuli config: en split: test metrics: - type: wer value: 11.31 name: WER pipeline_tag: automatic-speech-recognition --- # Whisper tiny mixed-English This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the "en" datasets: - mozilla-foundation/common_voice_17_0 - google/fleurs - facebook/voxpopuli It achieves the following results on the evaluation set: - Loss: 0.6272 - Wer: 26.4827 ## 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: 64 - eval_batch_size: 16 - 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: 5000 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.3844 | 0.2 | 1000 | 0.6787 | 28.9037 | | 0.3104 | 0.4 | 2000 | 0.6485 | 27.1148 | | 0.3125 | 0.6 | 3000 | 0.6359 | 26.4310 | | 0.2607 | 0.8 | 4000 | 0.6310 | 26.3389 | | 0.2683 | 1.0 | 5000 | 0.6272 | 26.4827 | ### Framework versions - Transformers 4.42.0.dev0 - Pytorch 2.3.0+cu121 - Datasets 2.19.1 - Tokenizers 0.19.1