--- license: apache-2.0 tags: - audio-classification - generated_from_trainer datasets: - common_language metrics: - accuracy model-index: - name: distilhubert-ft-common-language results: [] --- # distilhubert-ft-common-language This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the common_language dataset. It achieves the following results on the evaluation set: - Loss: 2.7214 - Accuracy: 0.2797 ## 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: 32 - eval_batch_size: 4 - 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: 10.0 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 3.6543 | 1.0 | 173 | 3.7611 | 0.0491 | | 3.2221 | 2.0 | 346 | 3.4868 | 0.1352 | | 2.9332 | 3.0 | 519 | 3.2732 | 0.1861 | | 2.7299 | 4.0 | 692 | 3.0944 | 0.2172 | | 2.5638 | 5.0 | 865 | 2.9790 | 0.2400 | | 2.3871 | 6.0 | 1038 | 2.8668 | 0.2590 | | 2.3384 | 7.0 | 1211 | 2.7972 | 0.2653 | | 2.2648 | 8.0 | 1384 | 2.7625 | 0.2695 | | 2.2162 | 9.0 | 1557 | 2.7405 | 0.2782 | | 2.1915 | 10.0 | 1730 | 2.7214 | 0.2797 | ### Framework versions - Transformers 4.12.0.dev0 - Pytorch 1.9.1+cu111 - Datasets 1.14.0 - Tokenizers 0.10.3