emotion_recognition

This model is a fine-tuned version of dima806/bird_sounds_classification on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7880
  • Accuracy: 0.8249

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-06
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 50
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.7843 1.0 4899 0.9654 0.7514
0.6352 2.0 9798 0.9026 0.7955
0.0438 3.0 14697 0.8320 0.8037
0.443 4.0 19596 0.8014 0.8131
0.3585 5.0 24495 0.7880 0.8249

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.2
  • Tokenizers 0.19.1
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