Wavlm Finetuned SAVEE

--- library_name: transformers base_model: microsoft/wavlm-base-plus tags: - generated_from_trainer metrics: - accuracy model-index: - name: wavlm-finetuned-SAVEE results: [] --- <!-- 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. --> # wavlm-finetuned-SAVEE This model is a fine-tuned version of [microsoft/wavlm-base-plus](https://huggingface.co/microsoft/wavlm-base-plus) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.6940 - Accuracy: 0.3542 ## 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: 4 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 16 - optimizer: Use OptimizerNames.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_steps: 0.1 - num_epochs: 5 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 24 | 1.9312 | 0.2188 | | No log | 2.0 | 48 | 1.8608 | 0.3125 | | 7.6509 | 3.0 | 72 | 1.7555 | 0.3333 | | 7.6509 | 4.0 | 96 | 1.7167 | 0.3333 | | 6.9743 | 5.0 | 120 | 1.6940 | 0.3542 | ### Framework versions - Transformers 5.12.0 - Pytorch 2.11.0+cu128 - Datasets 5.0.0 - Tokenizers 0.22.2

Source context: 6 downloads · 0 likes · Pipeline audio-classification · Library transformers · Repo VasilisAsim/wavlm-finetuned-SAVEE

Source context: 5 downloads · 0 likes · Pipeline audio-classification · Library transformers · Repo VasilisAsim/wavlm-finetuned-SAVEE