--- base_model: openai/whisper-tiny license: apache-2.0 metrics: - wer tags: - generated_from_trainer model-index: - name: whisper-tinyf results: [] --- # whisper-tinyf This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.0000 - Wer: 0.0 ## 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: 16 - eval_batch_size: 1 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 100 - training_steps: 1000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:------:|:----:|:---------------:|:---:| | No log | 100.0 | 100 | 0.0001 | 0.0 | | No log | 200.0 | 200 | 0.0000 | 0.0 | | No log | 300.0 | 300 | 0.0000 | 0.0 | | No log | 400.0 | 400 | 0.0000 | 0.0 | | 0.006 | 500.0 | 500 | 0.0000 | 0.0 | | 0.006 | 600.0 | 600 | 0.0000 | 0.0 | | 0.006 | 700.0 | 700 | 0.0000 | 0.0 | | 0.006 | 800.0 | 800 | 0.0000 | 0.0 | | 0.006 | 900.0 | 900 | 0.0000 | 0.0 | | 0.0 | 1000.0 | 1000 | 0.0000 | 0.0 | ### Framework versions - Transformers 4.40.2 - Pytorch 2.2.1+cu121 - Datasets 2.19.1 - Tokenizers 0.19.1