--- license: apache-2.0 base_model: openai/whisper-small tags: - generated_from_trainer metrics: - wer model-index: - name: whisper-small-eng results: [] --- # whisper-small-eng This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.5746 - Wer: 24.4747 ## 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: 0.0001 - train_batch_size: 16 - eval_batch_size: 8 - seed: 42 - distributed_type: multi-GPU - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 50 - training_steps: 1000 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.7025 | 0.03 | 100 | 0.6855 | 36.9988 | | 0.7478 | 0.07 | 200 | 0.8034 | 35.4196 | | 0.7516 | 0.1 | 300 | 0.7854 | 31.8551 | | 0.7175 | 0.13 | 400 | 0.7868 | 32.9444 | | 0.6748 | 0.17 | 500 | 0.7239 | 31.1203 | | 0.6739 | 0.2 | 600 | 0.7045 | 29.7473 | | 0.6262 | 0.24 | 700 | 0.6620 | 27.1239 | | 0.585 | 0.27 | 800 | 0.6254 | 26.6147 | | 0.5305 | 0.3 | 900 | 0.5877 | 24.6552 | | 0.5463 | 0.34 | 1000 | 0.5746 | 24.4747 | ### Framework versions - Transformers 4.38.0.dev0 - Pytorch 2.1.2+cu121 - Datasets 2.16.1 - Tokenizers 0.15.1