--- library_name: transformers language: - en license: apache-2.0 base_model: openai/whisper-large-v3 tags: - wft - whisper - automatic-speech-recognition - audio - speech - generated_from_trainer datasets: - ntnu-smil/sandi2025-ds metrics: - wer model-index: - name: whisper-large-v3-sandi-7k-1024-28steps results: - task: type: automatic-speech-recognition name: Automatic Speech Recognition dataset: name: ntnu-smil/sandi2025-ds type: ntnu-smil/sandi2025-ds metrics: - type: wer value: 73.82367281180885 name: Wer --- # whisper-large-v3-sandi-7k-1024-28steps This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the ntnu-smil/sandi2025-ds dataset. It achieves the following results on the evaluation set: - Loss: 1.0275 - Wer: 73.8237 - Cer: 203.1654 - Decode Runtime: 257.7123 - Wer Runtime: 0.2072 - Cer Runtime: 0.4935 ## 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: 7e-05 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - gradient_accumulation_steps: 32 - total_train_batch_size: 1024 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.98) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - training_steps: 28 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | Cer | Decode Runtime | Wer Runtime | Cer Runtime | |:-------------:|:------:|:----:|:---------------:|:-------:|:--------:|:--------------:|:-----------:|:-----------:| | 1.9026 | 1.0357 | 7 | 1.3670 | 70.5577 | 206.9010 | 266.1791 | 0.2147 | 0.5053 | | 1.2477 | 2.0714 | 14 | 1.1783 | 86.2572 | 223.6346 | 268.9910 | 0.2241 | 0.5015 | | 1.07 | 3.1071 | 21 | 1.0605 | 78.7713 | 211.1141 | 262.5822 | 0.2186 | 0.5076 | | 1.0348 | 4.1429 | 28 | 1.0275 | 73.8237 | 203.1654 | 257.7123 | 0.2072 | 0.4935 | ### Framework versions - PEFT 0.15.2 - Transformers 4.51.3 - Pytorch 2.4.1+cu124 - Datasets 3.5.1 - Tokenizers 0.21.1