--- license: apache-2.0 base_model: openai/whisper-small.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-small.en](https://huggingface.co/openai/whisper-small.en) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.0002 - Wer: 1.5152 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:------:| | 1.1465 | 25.0 | 100 | 1.1124 | 9.6970 | | 0.4228 | 50.0 | 200 | 0.4547 | 2.4242 | | 0.0555 | 75.0 | 300 | 0.0459 | 1.8182 | | 0.0022 | 100.0 | 400 | 0.0022 | 1.8182 | | 0.0007 | 125.0 | 500 | 0.0008 | 1.5152 | | 0.0004 | 150.0 | 600 | 0.0005 | 1.5152 | | 0.0003 | 175.0 | 700 | 0.0003 | 1.5152 | | 0.0002 | 200.0 | 800 | 0.0003 | 1.5152 | | 0.0002 | 225.0 | 900 | 0.0003 | 1.5152 | | 0.0002 | 250.0 | 1000 | 0.0002 | 1.5152 | ### Framework versions - Transformers 4.41.0 - Pytorch 2.2.0a0+81ea7a4 - Datasets 2.19.1 - Tokenizers 0.19.1