--- language: - bn license: apache-2.0 base_model: openai/whisper-base tags: - whisper-event - generated_from_trainer datasets: - mozilla-foundation/common_voice_16_0 metrics: - wer model-index: - name: Whisper Base Bengali results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: mozilla-foundation/common_voice_16_0 bn type: mozilla-foundation/common_voice_16_0 config: bn split: test args: bn metrics: - name: Wer type: wer value: 37.010192120122056 --- # Whisper Base Bengali This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the mozilla-foundation/common_voice_16_0 bn dataset. It achieves the following results on the evaluation set: - Loss: 0.2823 - Wer: 37.0102 ## 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-06 - train_batch_size: 32 - eval_batch_size: 32 - 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: 500 - training_steps: 5000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.4236 | 3.03 | 1000 | 0.4400 | 50.4684 | | 0.3023 | 6.05 | 2000 | 0.3335 | 41.4718 | | 0.2721 | 10.02 | 3000 | 0.3005 | 38.6209 | | 0.2471 | 13.04 | 4000 | 0.2866 | 37.4478 | | 0.2574 | 17.01 | 5000 | 0.2823 | 37.0102 | ### Framework versions - Transformers 4.37.0.dev0 - Pytorch 2.1.2+cu121 - Datasets 2.16.2.dev0 - Tokenizers 0.15.0