--- tags: - generated_from_trainer metrics: - accuracy model-index: - name: unispeech-sat-base-ft results: [] datasets: - mazkooleg/0-9up_google_speech_commands_augmented_raw --- # unispeech-sat-base-ft This model is a fine-tuned version of [microsoft/unispeech-sat-base](https://huggingface.co/microsoft/unispeech-sat-base) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.0123 - Accuracy: 0.9979 ## 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: 32 - eval_batch_size: 32 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 128 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Accuracy | Validation Loss | |:-------------:|:-----:|:-----:|:--------:|:---------------:| | 0.0916 | 1.0 | 8558 | 0.9958 | 0.0174 | | 0.0592 | 2.0 | 17116 | 0.9979 | 0.0123 | | 0.0725 | 3.0 | 25674 | 0.9958 | 0.0196 | | 0.0585 | 4.0 | 34232 | 0.9955 | 0.0213 | | 0.0472 | 5.0 | 42790 | 0.9958 | 0.0212 | ### Framework versions - Transformers 4.27.1 - Pytorch 1.11.0 - Datasets 2.10.1 - Tokenizers 0.12.1