--- license: apache-2.0 tags: - generated_from_trainer datasets: - fleurs metrics: - wer model-index: - name: openai/whisper-medium results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: fleurs type: fleurs config: ps_af split: test args: ps_af metrics: - name: Wer type: wer value: 63.10532687651331 --- # openai/whisper-medium This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the fleurs dataset. It achieves the following results on the evaluation set: - Loss: 1.0063 - Wer: 63.1053 ## 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: 3e-07 - train_batch_size: 32 - eval_batch_size: 16 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 64 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 10 - training_steps: 700 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 1.4728 | 14.29 | 100 | 1.4429 | 83.5942 | | 1.0344 | 28.57 | 200 | 1.1584 | 69.9706 | | 0.9318 | 42.86 | 300 | 1.1061 | 67.8394 | | 0.8882 | 57.14 | 400 | 1.0769 | 66.4290 | | 0.8609 | 71.43 | 500 | 1.0575 | 66.1965 | | 0.8262 | 85.71 | 600 | 1.0214 | 63.6274 | | 0.7989 | 100.0 | 700 | 1.0063 | 63.1053 | ### Framework versions - Transformers 4.26.0.dev0 - Pytorch 1.13.0+cu117 - Datasets 2.7.1.dev0 - Tokenizers 0.13.2