Wavlm Finetuned IEMOCAP

--- library_name: transformers base_model: microsoft/wavlm-base-plus tags: - generated_from_trainer metrics: - accuracy model-index: - name: wavlm-finetuned-IEMOCAP 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-IEMOCAP 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: 1.4042 - Accuracy: 0.4972 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 6.8687 | 1.0 | 402 | 1.7019 | 0.3292 | | 6.5214 | 2.0 | 804 | 1.6125 | 0.3671 | | 5.9374 | 3.0 | 1206 | 1.5022 | 0.4493 | | 5.4183 | 4.0 | 1608 | 1.4527 | 0.4798 | | 5.2812 | 5.0 | 2010 | 1.4042 | 0.4972 | ### Framework versions - Transformers 5.12.0 - Pytorch 2.11.0+cu128 - Datasets 5.0.0 - Tokenizers 0.22.2

Source context: 43 downloads · 0 likes · Pipeline audio-classification · Library transformers · Repo VasilisAsim/wavlm-finetuned-IEMOCAP

Source context: 7 downloads · 0 likes · Pipeline audio-classification · Library transformers · Repo VasilisAsim/wavlm-finetuned-IEMOCAP