--- tags: - audio-classification - generated_from_trainer datasets: - superb metrics: - accuracy base_model: vumichien/nonsemantic-speech-trillsson3 model-index: - name: trillsson3-ft-keyword-spotting-11 results: [] --- # trillsson3-ft-keyword-spotting-11 This model is a fine-tuned version of [vumichien/nonsemantic-speech-trillsson3](https://huggingface.co/vumichien/nonsemantic-speech-trillsson3) on the superb dataset. It achieves the following results on the evaluation set: - Loss: 0.3166 - Accuracy: 0.9088 ## 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: 0.0003 - train_batch_size: 32 - eval_batch_size: 32 - seed: 0 - 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: 20.0 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 2.9219 | 1.0 | 399 | 1.2023 | 0.6217 | | 0.9604 | 2.0 | 798 | 0.5437 | 0.8117 | | 0.7608 | 3.0 | 1197 | 0.4222 | 0.8888 | | 0.7045 | 4.0 | 1596 | 0.3881 | 0.8932 | | 0.659 | 5.0 | 1995 | 0.3706 | 0.8847 | | 0.6541 | 6.0 | 2394 | 0.3553 | 0.8917 | | 0.6448 | 7.0 | 2793 | 0.3482 | 0.8953 | | 0.6288 | 8.0 | 3192 | 0.3409 | 0.8989 | | 0.641 | 9.0 | 3591 | 0.3297 | 0.9051 | | 0.6369 | 10.0 | 3990 | 0.3325 | 0.9042 | | 0.6218 | 11.0 | 4389 | 0.3250 | 0.9064 | | 0.6247 | 12.0 | 4788 | 0.3312 | 0.8959 | | 0.6284 | 13.0 | 5187 | 0.3217 | 0.9069 | | 0.6213 | 14.0 | 5586 | 0.3301 | 0.8978 | | 0.6274 | 15.0 | 5985 | 0.3180 | 0.9081 | | 0.627 | 16.0 | 6384 | 0.3257 | 0.9020 | | 0.6227 | 17.0 | 6783 | 0.3193 | 0.9056 | | 0.6192 | 18.0 | 7182 | 0.3199 | 0.9066 | | 0.6075 | 19.0 | 7581 | 0.3183 | 0.9073 | | 0.6196 | 20.0 | 7980 | 0.3166 | 0.9088 | ### Framework versions - Transformers 4.23.0.dev0 - Pytorch 1.12.1+cu113 - Datasets 2.6.1 - Tokenizers 0.13.1