--- language: - fi license: apache-2.0 tags: - whisper-event - generated_from_trainer datasets: - mozilla-foundation/common_voice_11_0 model-index: - name: Whisper Medium Fi - Teemu Sormunen results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 11.0 type: mozilla-foundation/common_voice_11_0 config: fi split: test args: fi metrics: - name: Wer type: wer value: 16.3871 --- # Whisper Medium Fi - Teemu Sormunen This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 11.0, train+val dataset. It achieves the following results on the evaluation set: - eval_loss: 0.2453 - eval_wer: 16.3871 - eval_runtime: 1296.4339 - eval_samples_per_second: 1.314 - eval_steps_per_second: 0.164 - epoch: 5.04 - step: 300 ## Model description Checkpoint of a Finnish model trained with Common Voice 11.0 train+validation data. The data is very small, and already during 300 steps the model overfit on training data. ## 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: 32 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 64 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 300 - training_steps: 1000 - mixed_precision_training: Native AMP ### Framework versions - Transformers 4.26.0.dev0 - Pytorch 1.13.0+cu117 - Datasets 2.7.1.dev0 - Tokenizers 0.13.2