Wav2vec2 Large Xlsr 53 Th Speech Emotion Recognition 3c

🚀 wav2vec2-large-xlsr-53-th-speech-emotion-recognition-3c

This model is a fine - tuned speech emotion recognition model based on the wav2vec2 architecture, capable of classifying three emotions.

🚀 Quick Start

This model is a fine-tuned version of airesearch/wav2vec2-large-xlsr-53-th on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.4445
• Accuracy: 0.8492

✨ Features

• Emotion Classification: This model can classify three emotions: Anger, Happiness, and Neutral.

📚 Documentation

Model description

This model can classify three emotions: [Anger, Happiness, Neutral].

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: 32
• eval_batch_size: 32
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 128
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 20

Training results

Framework versions

• Transformers 4.44.2
• Pytorch 2.4.1+cu121
• Datasets 3.0.1
• Tokenizers 0.19.1

📄 License

This model is licensed under cc-by-sa-4.0.