--- language: - es license: apache-2.0 tags: - hf-asr-leaderboard - generated_from_trainer datasets: - facebook/multilingual_librispeech metrics: - wer model-index: - name: Whisper Small Es - Sanchit Gandhi results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Multilingual LibriSpeech type: facebook/multilingual_librispeech args: 'config: es, split: test' metrics: - name: Wer type: wer value: 4.037333755183674 --- # Whisper Small Es - Sanchit Gandhi This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Multilingual LibriSpeech dataset. It achieves the following results on the evaluation set: - Loss: 0.1035 - Wer: 4.0373 ## 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: 4 - seed: 42 - gradient_accumulation_steps: 16 - total_train_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - training_steps: 4000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:------:| | 0.1947 | 0.25 | 1000 | 0.1390 | 5.8261 | | 0.1226 | 0.5 | 2000 | 0.1224 | 4.9978 | | 0.1629 | 0.75 | 3000 | 0.1185 | 4.6543 | | 0.1916 | 1.0 | 4000 | 0.1035 | 4.0373 | ### Framework versions - Transformers 4.25.0.dev0 - Pytorch 1.12.0 - Datasets 2.6.2.dev0 - Tokenizers 0.12.1