--- license: bsd-3-clause base_model: MIT/ast-finetuned-speech-commands-v2 tags: - generated_from_trainer metrics: - accuracy model-index: - name: right4-ast-finetuned-speech-commands-v2-poisoned results: [] --- # right4-ast-finetuned-speech-commands-v2-poisoned This model is a fine-tuned version of [MIT/ast-finetuned-speech-commands-v2](https://huggingface.co/MIT/ast-finetuned-speech-commands-v2) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.8907 - Accuracy: 0.7730 ## 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: 3e-05 - train_batch_size: 22 - eval_batch_size: 22 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 88 - 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 | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 0.86 | 3 | 7.0518 | 0.0 | | No log | 2.0 | 7 | 2.9004 | 0.0099 | | 6.0247 | 2.86 | 10 | 1.6879 | 0.2796 | | 6.0247 | 4.0 | 14 | 0.9386 | 0.7599 | | 6.0247 | 4.29 | 15 | 0.8907 | 0.7730 | ### Framework versions - Transformers 4.37.0 - Pytorch 2.1.2 - Datasets 2.16.1 - Tokenizers 0.15.1