--- license: apache-2.0 tags: - generated_from_trainer datasets: - minds14 metrics: - accuracy model-index: - name: audio_cls_unispeech-sat-base-100h-libri-ft_minds14_finetune results: [] --- # audio_cls_unispeech-sat-base-100h-libri-ft_minds14_finetune This model is a fine-tuned version of [microsoft/unispeech-sat-base-100h-libri-ft](https://huggingface.co/microsoft/unispeech-sat-base-100h-libri-ft) on the minds14 dataset. It achieves the following results on the evaluation set: - Loss: 2.6384 - Accuracy: 0.0708 ## 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: 64 - eval_batch_size: 64 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 256 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 2 | 2.6385 | 0.0442 | | No log | 2.0 | 4 | 2.6385 | 0.0796 | | No log | 3.0 | 6 | 2.6386 | 0.0619 | | No log | 4.0 | 8 | 2.6375 | 0.0531 | | 2.64 | 5.0 | 10 | 2.6372 | 0.0619 | | 2.64 | 6.0 | 12 | 2.6376 | 0.0708 | | 2.64 | 7.0 | 14 | 2.6379 | 0.0708 | | 2.64 | 8.0 | 16 | 2.6381 | 0.0708 | | 2.64 | 9.0 | 18 | 2.6384 | 0.0708 | | 2.638 | 10.0 | 20 | 2.6384 | 0.0708 | ### Framework versions - Transformers 4.29.2 - Pytorch 2.0.1+cu117 - Datasets 2.12.0 - Tokenizers 0.13.3