--- language: - hi license: apache-2.0 tags: - whisper-event - generated_from_trainer datasets: - mozilla-foundation/common_voice_11_0 metrics: - wer model-index: - name: WhpTiny-hi-v2 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: test args: hi metrics: - name: Wer type: wer value: 43.666169895678095 --- # WhpTiny-hi-v2 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set: - Loss: 1.0825 - Wer: 43.6662 ## 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 - gradient_accumulation_steps: 2 - total_train_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - training_steps: 5000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.1627 | 7.01 | 1000 | 0.5714 | 40.9378 | | 0.0275 | 14.02 | 2000 | 0.7620 | 42.5943 | | 0.0032 | 22.0 | 3000 | 0.9561 | 43.0443 | | 0.0012 | 29.01 | 4000 | 1.0517 | 43.4426 | | 0.0008 | 36.02 | 5000 | 1.0825 | 43.6662 | ### Framework versions - Transformers 4.26.0.dev0 - Pytorch 1.10.0 - Datasets 2.7.1.dev0 - Tokenizers 0.13.2