--- language: - hi license: apache-2.0 tags: - generated_from_trainer base_model: Aakali/whisper-medium-hi datasets: - mozilla-foundation/common_voice_11_0 metrics: - wer model-index: - name: Whisper medium-translate Hi - Aa results: - task: type: automatic-speech-recognition name: Automatic Speech Recognition dataset: name: Common Voice 11.0 type: mozilla-foundation/common_voice_11_0 args: 'config: hi, split: test' metrics: - type: wer value: 48.11612382957753 name: Wer --- # Whisper medium-translate Hi - Aa This model is a fine-tuned version of [Aakali/whisper-medium-hi](https://huggingface.co/Aakali/whisper-medium-hi) on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set: - Loss: 0.9904 - Wer: 48.1161 ## 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: 5000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-------:|:----:|:---------------:|:-------:| | 0.1405 | 2.4450 | 1000 | 0.7580 | 51.5075 | | 0.0245 | 4.8900 | 2000 | 0.8571 | 51.4000 | | 0.0026 | 7.3350 | 3000 | 0.9280 | 48.3132 | | 0.0011 | 9.7800 | 4000 | 0.9673 | 47.6457 | | 0.0006 | 12.2249 | 5000 | 0.9904 | 48.1161 | ### Framework versions - Transformers 4.41.0 - Pytorch 2.2.1+cu121 - Datasets 2.19.1 - Tokenizers 0.19.1