Whisper Finetuned Casia

--- library_name: transformers base_model: BurningFang/finetuned_whisper_for_speech_emotion_recognition_optimised tags: - generated_from_trainer datasets: - audiofolder metrics: - accuracy model-index: - name: whisper-finetuned-Casia results: - task: name: Audio Classification type: audio-classification dataset: name: audiofolder type: audiofolder config: default split: train args: default metrics: - name: Accuracy type: accuracy value: 0.9166666666666666 --- <!-- 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. --> # whisper-finetuned-Casia This model is a fine-tuned version of [BurningFang/finetuned_whisper_for_speech_emotion_recognition_optimised](https://huggingface.co/BurningFang/finetuned_whisper_for_speech_emotion_recognition_optimised) on the audiofolder dataset. It achieves the following results on the evaluation set: - Loss: 0.3075 - Accuracy: 0.9167 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 5.7654 | 1.0 | 60 | 0.8018 | 0.6917 | | 2.1920 | 2.0 | 120 | 0.6170 | 0.7625 | | 1.2518 | 3.0 | 180 | 0.5152 | 0.8167 | | 0.6786 | 4.0 | 240 | 0.3177 | 0.9 | | 0.0600 | 5.0 | 300 | 0.3075 | 0.9167 | ### Framework versions - Transformers 5.0.0 - Pytorch 2.11.0+cu128 - Datasets 4.0.0 - Tokenizers 0.22.2

Source context: 3 downloads · 0 likes · Pipeline audio-classification · Library transformers · Repo VasilisAsim/whisper-finetuned-Casia

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