--- language: - mr license: apache-2.0 base_model: simran14/small_8_a tags: - generated_from_trainer datasets: - mozilla-foundation/common_voice_11_0 metrics: - wer model-index: - name: simrank14 Whisper small 1B 8e results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 11.0 type: mozilla-foundation/common_voice_11_0 config: mr split: test args: mr metrics: - name: Wer type: wer value: 18.890597961930396 library_name: transformers pipeline_tag: automatic-speech-recognition --- # simrank14 Whisper small 1B 8e This model is a fine-tuned version of [simran14/small_8_a](https://huggingface.co/simran14/small_8_a) on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set: - Loss: 0.5179 - Wer: 18.8906 ## 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: 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: 8 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:------:|:----:|:---------------:|:-------:| | 0.003 | 3.5587 | 1000 | 0.4735 | 19.5011 | | 0.0002 | 7.1174 | 2000 | 0.5179 | 18.8906 | ### Framework versions - Transformers 4.45.0.dev0 - Pytorch 2.3.1+cu121 - Datasets 2.20.1.dev0 - Tokenizers 0.19.1