--- language: - ru license: apache-2.0 tags: - generated_from_trainer base_model: openai/whisper-tiny datasets: - bond005/podlodka_speech metrics: - wer model-index: - name: whisper-tiny-ru results: - task: type: automatic-speech-recognition name: Automatic Speech Recognition dataset: name: Podlodka Speech type: bond005/podlodka_speech args: 'config: ru, split: test' metrics: - type: wer value: 99.38757655293088 name: Wer --- # whisper-tiny-ru This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Podlodka Speech dataset. It achieves the following results on the evaluation set: - Loss: 1.4991 - Wer: 99.3876 ## 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: 8 - eval_batch_size: 4 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 100 - training_steps: 500 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-------:|:----:|:---------------:|:--------:| | 0.295 | 5.5556 | 50 | 1.1982 | 83.2896 | | 0.1297 | 11.1111 | 100 | 1.2768 | 76.0280 | | 0.0517 | 16.6667 | 150 | 1.3594 | 72.5284 | | 0.0203 | 22.2222 | 200 | 1.3969 | 85.4768 | | 0.0094 | 27.7778 | 250 | 1.4394 | 104.2870 | | 0.0061 | 33.3333 | 300 | 1.4646 | 87.8390 | | 0.0049 | 38.8889 | 350 | 1.4813 | 90.4637 | | 0.0043 | 44.4444 | 400 | 1.4909 | 86.7017 | | 0.004 | 50.0 | 450 | 1.4973 | 99.6500 | | 0.0038 | 55.5556 | 500 | 1.4991 | 99.3876 | ### Framework versions - Transformers 4.40.2 - Pytorch 2.2.1+cu121 - Datasets 2.19.1 - Tokenizers 0.19.1