--- language: - tr license: apache-2.0 tags: - hf-asr-leaderboard - generated_from_trainer metrics: - wer model-index: - name: base Turkish Whisper (bTW) results: [] --- # base Turkish Whisper (bTW) This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Ermetal Meetings dataset. It achieves the following results on the evaluation set: - Loss: 1.8804 - Wer: 2.0146 - Cer: 1.4030 ## 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: 16 - seed: 42 - gradient_accumulation_steps: 4 - 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: 500 - training_steps: 1000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |:-------------:|:------:|:----:|:---------------:|:------:|:------:| | 1.4622 | 16.67 | 100 | 1.5376 | 0.8662 | 0.7357 | | 0.297 | 33.33 | 200 | 1.2979 | 0.8675 | 0.6481 | | 0.0163 | 50.0 | 300 | 1.5699 | 1.4066 | 1.0449 | | 0.0034 | 66.67 | 400 | 1.6919 | 1.6416 | 1.1817 | | 0.0017 | 83.33 | 500 | 1.7654 | 1.6943 | 1.2587 | | 0.0011 | 100.0 | 600 | 1.8153 | 1.9908 | 1.4084 | | 0.0008 | 116.67 | 700 | 1.8455 | 1.9817 | 1.3867 | | 0.0007 | 133.33 | 800 | 1.8647 | 2.0479 | 1.4215 | | 0.0006 | 150.0 | 900 | 1.8764 | 2.0489 | 1.4253 | | 0.0006 | 166.67 | 1000 | 1.8804 | 2.0146 | 1.4030 | ### Framework versions - Transformers 4.26.0 - Pytorch 1.12.0+cu102 - Datasets 2.9.0 - Tokenizers 0.13.2