--- license: apache-2.0 base_model: facebook/hubert-large-ll60k tags: - audio-classification - generated_from_trainer datasets: - superb metrics: - accuracy model-index: - name: superb_ks_42 results: - task: name: Audio Classification type: audio-classification dataset: name: superb type: superb config: ks split: validation args: ks metrics: - name: Accuracy type: accuracy value: 0.6209179170344219 --- # superb_ks_42 This model is a fine-tuned version of [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) on the superb dataset. It achieves the following results on the evaluation set: - Loss: -9.0111 - Accuracy: 0.6209 - Test Accuracy: 0.6209 - Df Accuracy: 0.1395 - Unlearn Overall Accuracy: 0.7407 - Unlearn Time: 929.3382 ## 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: 5e-05 - train_batch_size: 32 - eval_batch_size: 8 - seed: 42 - 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 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | Overall Accuracy | Unlearn Overall Accuracy | Time | |:-------------:|:-----:|:----:|:---------------:|:--------:|:----------------:|:------------------------:|:----:| | No log | 1.0 | 128 | -9.0111 | 0.1395 | 0.7407 | 0.7407 | -1 | | No log | 2.0 | 256 | -20.9958 | 0.1395 | 0.7407 | 0.7407 | -1 | | No log | 3.0 | 384 | -35.4087 | 0.1395 | 0.7407 | 0.7407 | -1 | | No log | 4.0 | 512 | -51.3901 | 0.1395 | 0.7407 | 0.7407 | -1 | | No log | 5.0 | 640 | -67.7050 | 0.1395 | 0.7407 | 0.7407 | -1 | | No log | 6.0 | 768 | -83.0873 | 0.1395 | 0.7407 | 0.7407 | -1 | | No log | 7.0 | 896 | -96.3518 | 0.1395 | 0.7407 | 0.7407 | -1 | | -113.6834 | 8.0 | 1024 | -106.5309 | 0.1395 | 0.7407 | 0.7407 | -1 | | -113.6834 | 9.0 | 1152 | -112.9372 | 0.1395 | 0.7407 | 0.7407 | -1 | | -113.6834 | 10.0 | 1280 | -115.1336 | 0.1395 | 0.7407 | 0.7407 | -1 | ### Framework versions - Transformers 4.39.3 - Pytorch 2.2.2+cu118 - Datasets 2.18.0 - Tokenizers 0.15.2