--- license: apache-2.0 base_model: openai/whisper-medium.en tags: - generated_from_trainer metrics: - wer model-index: - name: whisper-small-hi results: [] --- # whisper-small-hi This model is a fine-tuned version of [openai/whisper-medium.en](https://huggingface.co/openai/whisper-medium.en) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.0017 - Wer: 1.3384 ## 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: 500 - training_steps: 1000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-------:|:----:|:---------------:|:-------:| | 2.7899 | 4.1667 | 100 | 2.3530 | 21.4149 | | 0.8377 | 8.3333 | 200 | 0.7500 | 4.2065 | | 0.0599 | 12.5 | 300 | 0.0394 | 1.9120 | | 0.0163 | 16.6667 | 400 | 0.0151 | 2.1033 | | 0.0068 | 20.8333 | 500 | 0.0023 | 1.1472 | | 0.0031 | 25.0 | 600 | 0.0018 | 1.3384 | | 0.0027 | 29.1667 | 700 | 0.0023 | 1.3384 | | 0.0018 | 33.3333 | 800 | 0.0020 | 1.3384 | | 0.003 | 37.5 | 900 | 0.0017 | 1.3384 | | 0.0009 | 41.6667 | 1000 | 0.0017 | 1.3384 | ### Framework versions - Transformers 4.41.2 - Pytorch 2.3.0a0+ebedce2 - Datasets 2.19.2 - Tokenizers 0.19.1