--- 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: ko split: None args: 'config: hi, split: test' metrics: - name: Wer type: wer value: 38.57142857142858 --- # 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: 0.5393 - Wer: 38.5714 ## 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: 2 - eval_batch_size: 2 - 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: 4000 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-------:|:----:|:---------------:|:-------:| | 0.0003 | 16.1290 | 1000 | 0.4805 | 37.1429 | | 0.0001 | 32.2581 | 2000 | 0.5145 | 38.0952 | | 0.0001 | 48.3871 | 3000 | 0.5327 | 38.5714 | | 0.0 | 64.5161 | 4000 | 0.5393 | 38.5714 | ### Framework versions - Transformers 4.40.1 - Pytorch 2.2.1+cu121 - Datasets 2.19.0 - Tokenizers 0.19.1