--- library_name: transformers language: - hi license: apache-2.0 base_model: openai/whisper-small tags: - generated_from_trainer datasets: - mozilla-foundation/common_voice_11_0 metrics: - wer model-index: - name: Whisper Small Hi - Sanchit Gandhi results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 11.0 type: mozilla-foundation/common_voice_11_0 config: hi split: None args: 'config: hi, split: test' metrics: - name: Wer type: wer value: 53.309912807923475 --- # Whisper Small Hi - Sanchit Gandhi This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set: - Loss: 0.5063 - Wer: 53.3099 ## 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: 5 - training_steps: 40 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:------:|:----:|:---------------:|:-------:| | No log | 0.0244 | 10 | 0.6725 | 61.2630 | | No log | 0.0489 | 20 | 0.5616 | 58.4102 | | 0.6508 | 0.0733 | 30 | 0.5177 | 54.1437 | | 0.6508 | 0.0978 | 40 | 0.5063 | 53.3099 | ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.0+cu121 - Datasets 3.0.0 - Tokenizers 0.19.1