--- license: apache-2.0 tags: - generated_from_trainer datasets: - fleurs metrics: - wer model-index: - name: whisper-training-blog results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: fleurs type: fleurs config: sv_se split: validation args: sv_se metrics: - name: Wer type: wer value: 191.23423279578478 --- # whisper-training-blog This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the fleurs dataset. It achieves the following results on the evaluation set: - Loss: 1.0050 - Wer: 191.2342 ## 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: 7.5e-06 - train_batch_size: 16 - 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_ratio: 0.3 - training_steps: 448 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 1.4111 | 0.1 | 44 | 1.4919 | 245.3457 | | 1.0501 | 0.2 | 88 | 1.2255 | 225.8822 | | 0.9032 | 0.29 | 132 | 1.1203 | 211.6558 | | 0.8141 | 1.06 | 176 | 1.0675 | 184.6240 | | 0.8029 | 1.16 | 220 | 1.0394 | 178.4129 | | 0.6325 | 1.25 | 264 | 1.0301 | 216.6374 | | 0.6971 | 2.02 | 308 | 1.0135 | 184.4004 | | 0.6051 | 2.12 | 352 | 1.0065 | 194.7150 | | 0.6047 | 2.21 | 396 | 1.0029 | 166.9328 | | 0.585 | 2.31 | 440 | 1.0050 | 191.2342 | ### Framework versions - Transformers 4.29.2 - Pytorch 2.0.1+cu118 - Datasets 2.12.0 - Tokenizers 0.13.3