--- license: apache-2.0 base_model: ntu-spml/distilhubert tags: - generated_from_trainer datasets: - thisisjibon/banglabeats metrics: - accuracy model-index: - name: distilhubert-finetuned-banglabeats results: - task: name: Audio Classification type: audio-classification dataset: name: BanglaBeats type: thisisjibon/banglabeats config: all split: train args: all metrics: - name: Accuracy type: accuracy value: 0.8336425479282622 --- # distilhubert-finetuned-banglabeats This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the BanglaBeats dataset. It achieves the following results on the evaluation set: - Loss: 1.4126 - Accuracy: 0.8336 ## 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: 6e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 16 - 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 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:-----:|:---------------:|:--------:| | 0.9439 | 1.0 | 910 | 0.9274 | 0.6425 | | 0.854 | 2.0 | 1820 | 0.7498 | 0.7260 | | 0.4835 | 3.0 | 2730 | 0.6329 | 0.7706 | | 0.6226 | 4.0 | 3640 | 0.6159 | 0.7934 | | 0.456 | 5.0 | 4550 | 0.7118 | 0.7972 | | 0.0565 | 6.0 | 5460 | 0.7994 | 0.8052 | | 0.2605 | 7.0 | 6370 | 0.9735 | 0.8151 | | 0.3635 | 8.0 | 7280 | 1.0618 | 0.8244 | | 0.1879 | 9.0 | 8190 | 1.1644 | 0.8213 | | 0.0292 | 10.0 | 9100 | 1.2543 | 0.8194 | | 0.0002 | 11.0 | 10010 | 1.4084 | 0.8101 | | 0.0006 | 12.0 | 10920 | 1.3823 | 0.8132 | | 0.088 | 13.0 | 11830 | 1.4016 | 0.8256 | | 0.0381 | 14.0 | 12740 | 1.3587 | 0.8225 | | 0.0 | 15.0 | 13650 | 1.4242 | 0.8169 | | 0.0 | 16.0 | 14560 | 1.4053 | 0.8275 | | 0.0183 | 17.0 | 15470 | 1.4357 | 0.8318 | | 0.0 | 18.0 | 16380 | 1.4123 | 0.8306 | | 0.0098 | 19.0 | 17290 | 1.4077 | 0.8330 | | 0.0 | 20.0 | 18200 | 1.4126 | 0.8336 | ### Framework versions - Transformers 4.33.0 - Pytorch 2.0.0 - Datasets 2.1.0 - Tokenizers 0.13.3