--- library_name: transformers language: - mr license: apache-2.0 base_model: simran14/mr-val-c tags: - generated_from_trainer datasets: - mozilla-foundation/common_voice_17_0 metrics: - wer model-index: - name: simrank14 Whisper small valD3 results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 17.0 type: mozilla-foundation/common_voice_17_0 config: mr split: test args: mr metrics: - name: Wer type: wer value: 0.767911727428614 --- # simrank14 Whisper small valD3 This model is a fine-tuned version of [simran14/mr-val-c](https://huggingface.co/simran14/mr-val-c) on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set: - Loss: 0.0098 - Wer: 0.7679 ## 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: 5e-07 - train_batch_size: 8 - 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: 100 - num_epochs: 2 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:------:|:----:|:---------------:|:------:| | 0.0119 | 0.7337 | 1000 | 0.0119 | 0.8947 | | 0.0093 | 1.4674 | 2000 | 0.0098 | 0.7679 | ### Framework versions - Transformers 4.45.0.dev0 - Pytorch 2.3.1+cu121 - Datasets 2.21.1.dev0 - Tokenizers 0.19.1