Wav2vec2 Base 100k Voxpopuli Finetuned Gtzan

--- library_name: transformers license: cc-by-nc-4.0 base_model: facebook/wav2vec2-base-100k-voxpopuli tags: - generated_from_trainer datasets: - marsyas/gtzan metrics: - accuracy model-index: - name: wav2vec2-base-100k-voxpopuli-finetuned-gtzan results: - task: name: Audio Classification type: audio-classification dataset: name: GTZAN type: marsyas/gtzan config: all split: train args: all metrics: - name: Accuracy type: accuracy value: 0.84 --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # wav2vec2-base-100k-voxpopuli-finetuned-gtzan This model is a fine-tuned version of [facebook/wav2vec2-base-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-base-100k-voxpopuli) on the GTZAN dataset. It achieves the following results on the evaluation set: - Loss: 1.0838 - Accuracy: 0.84 ## 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: 1e-05 - train_batch_size: 128 - eval_batch_size: 128 - seed: 42 - optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 10 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.0777 | 1.0 | 8 | 0.9974 | 0.86 | | 0.0276 | 2.0 | 16 | 1.1353 | 0.83 | | 0.326 | 3.0 | 24 | 1.2362 | 0.81 | | 0.123 | 4.0 | 32 | 1.1119 | 0.84 | | 0.0225 | 5.0 | 40 | 1.1009 | 0.85 | | 0.0776 | 6.0 | 48 | 1.0709 | 0.85 | | 0.025 | 7.0 | 56 | 1.1126 | 0.84 | | 0.0163 | 8.0 | 64 | 1.0823 | 0.84 | | 0.0193 | 9.0 | 72 | 1.0818 | 0.84 | | 0.0209 | 10.0 | 80 | 1.0838 | 0.84 | ### Framework versions - Transformers 4.57.3 - Pytorch 2.9.0+cu128 - Datasets 3.6.0 - Tokenizers 0.22.1