--- license: apache-2.0 base_model: openai/whisper-small tags: - generated_from_trainer datasets: - common_voice_13_0 metrics: - wer model-index: - name: whisper-id-finetuned-revised results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: common_voice_13_0 type: common_voice_13_0 config: id split: validation args: id metrics: - name: Wer type: wer value: 18.470763265858167 --- # whisper-id-finetuned-revised This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the common_voice_13_0 dataset. It achieves the following results on the evaluation set: - Loss: 0.3528 - Wer Ortho: 22.8496 - Wer: 18.4708 ## 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: 50 - training_steps: 1000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer | |:-------------:|:------:|:----:|:---------------:|:---------:|:-------:| | 0.3546 | 0.7911 | 250 | 0.3433 | 23.8195 | 18.6421 | | 0.1621 | 1.5823 | 500 | 0.3325 | 23.2594 | 18.9171 | | 0.058 | 2.3734 | 750 | 0.3483 | 23.1274 | 18.0966 | | 0.0265 | 3.1646 | 1000 | 0.3528 | 22.8496 | 18.4708 | ### Framework versions - Transformers 4.41.2 - Pytorch 2.3.0+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1