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Whisper Finetuned SAVEE

This model is a fine-tuned version of BurningFang/finetunedwhisperforspeechemotionrecognitionoptimised on an unknown dataset. It achieves the following results on the evaluation set: Loss: 0.4934 Accuracy: 0.8542

ArtModellBasismodellBurningFang/finetuned_whisper_for_speech_emotion_recognition_optimisedVersionRevision f8c07e7BBewertung

Modellquelle

Art
Modell
Dateigröße
79,1 MB
Basismodell
BurningFang/finetuned_whisper_for_speech_emotion_recognition_optimised
Version
vRevision f8c07e7
Aktualisiert
25. Okt. 2026
Downloads
37
Quelle
Hugging Face

Quellenbeschreibung

whisper-finetuned-SAVEE

This model is a fine-tuned version of BurningFang/finetuned_whisper_for_speech_emotion_recognition_optimised on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4934
  • Accuracy: 0.8542

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 LossEpochStepValidation LossAccuracy
No log1.0241.18510.5625
No log2.0480.89120.7083
6.49373.0720.61270.8021
6.49374.0960.49340.8542
0.12645.01200.51520.8333

Framework versions

  • Transformers 5.9.0
  • Pytorch 2.11.0+cu128
  • Datasets 4.8.5
  • Tokenizers 0.22.2

Quellen

1 Quelle
Hugging FacePrimärVersion f8c07e79ff8b4a56a31e9e698527279739c911ab
huggingface.co/VasilisAsim/whisper-finetuned-SAVEE/tree/f8c07e79ff8b4a56a31e9e698527279739c911ab

Verifiziert 25. Okt.

Modellartefakte

1 Artefakt

model.safetensors

safetensors · 79,1 MB · SHA-256 57ecbc446dfb…2dfa · Hugging Face

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Quellenauszüge

3 Auszüge

--- library_name: transformers base_model: BurningFang/finetuned_whisper_for_speech_emotion_recognition_optimised tags: - generated_from_trainer metrics: - accuracy model-index: - name: whisper-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. --> # whisper-finetuned-SAVEE 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 an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.4934 - Accuracy: 0.8542 ## 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 | 1.1851 | 0.5625 | | No log | 2.0 | 48 | 0.8912 | 0.7083 | | 6.4937 | 3.0 | 72 | 0.6127 | 0.8021 | | 6.4937 | 4.0 | 96 | 0.4934 | 0.8542 | | 0.1264 | 5.0 | 120 | 0.5152 | 0.8333 | ### Framework versions - Transformers 5.9.0 - Pytorch 2.11.0+cu128 - Datasets 4.8.5 - Tokenizers 0.22.2

Source context: 37 downloads · 0 likes · Pipeline audio-classification · Library transformers · Repo VasilisAsim/whisper-finetuned-SAVEE

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