--- 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: 1.8564 - Wer: 1.2482 - Cer: 0.7381 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:| | 1.6604 | 2.86 | 100 | 1.9378 | 1.1296 | 0.6334 | | 0.6453 | 5.71 | 200 | 1.4655 | 0.9878 | 0.5974 | | 0.3912 | 8.57 | 300 | 1.4669 | 1.2543 | 0.7557 | | 0.2081 | 11.43 | 400 | 1.4622 | 0.8203 | 0.5123 | | 0.094 | 14.29 | 500 | 1.6592 | 0.9535 | 0.6367 | | 0.039 | 17.14 | 600 | 1.6946 | 0.9658 | 0.5706 | | 0.0172 | 20.0 | 700 | 1.8271 | 1.4046 | 1.0027 | | 0.0086 | 22.86 | 800 | 1.8149 | 1.2567 | 0.7530 | | 0.0064 | 25.71 | 900 | 1.8478 | 1.2311 | 0.7279 | | 0.0061 | 28.57 | 1000 | 1.8564 | 1.2482 | 0.7381 | ### Framework versions - Transformers 4.26.0 - Pytorch 1.12.0+cu102 - Datasets 2.9.0 - Tokenizers 0.13.2