--- language: - ba license: apache-2.0 tags: - whisper-event - generated_from_trainer - hf-asr-leaderboard datasets: - mozilla-foundation/common_voice_11_0 metrics: - wer model-index: - name: Whisper Small Bashkir results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: mozilla-foundation/common_voice_11_0 ba type: mozilla-foundation/common_voice_11_0 config: ba split: test args: ba metrics: - name: Wer type: wer value: 15.072300680807968 --- # Whisper Small Bashkir This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0 ba dataset. It achieves the following results on the evaluation set: - Loss: 0.2589 - Wer: 15.0723 ## 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: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - training_steps: 30000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:-----:|:---------------:|:-------:| | 0.1637 | 1.01 | 2000 | 0.2555 | 26.4682 | | 0.1375 | 2.01 | 4000 | 0.2223 | 21.5394 | | 0.0851 | 3.02 | 6000 | 0.2086 | 19.6725 | | 0.0573 | 4.02 | 8000 | 0.2178 | 18.4280 | | 0.036 | 5.03 | 10000 | 0.2312 | 17.8248 | | 0.0238 | 6.04 | 12000 | 0.2621 | 17.4096 | | 0.0733 | 7.04 | 14000 | 0.2120 | 16.5656 | | 0.0111 | 8.05 | 16000 | 0.2682 | 16.2291 | | 0.0155 | 9.05 | 18000 | 0.2677 | 15.9242 | | 0.0041 | 10.06 | 20000 | 0.3178 | 15.9534 | | 0.0023 | 12.01 | 22000 | 0.3218 | 16.0536 | | 0.0621 | 13.01 | 24000 | 0.2313 | 15.6169 | | 0.0022 | 14.02 | 26000 | 0.2887 | 15.1083 | | 0.0199 | 15.02 | 28000 | 0.2553 | 15.1848 | | 0.0083 | 16.03 | 30000 | 0.2589 | 15.0723 | ### Framework versions - Transformers 4.26.0.dev0 - Pytorch 1.13.0+cu117 - Datasets 2.7.1.dev0 - Tokenizers 0.13.2