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wav2vec2-large-xlsr-53-english-finetuned-babycry-v3

Audio Classification
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wav2vec2-large-xlsr-53-english-finetuned-babycry-v3

This model is a fine-tuned version of jonatasgrosman/wav2vec2-large-xlsr-53-english on the audiofolder dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7337
  • Accuracy: {'accuracy': 0.8152173913043478}
  • F1: 0.7322
  • Precision: 0.6646
  • Recall: 0.8152

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: 0.001
  • train_batch_size: 4
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 8
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss Accuracy F1 Precision Recall
0.949 0.5435 25 0.7351 {'accuracy': 0.8152173913043478} 0.7322 0.6646 0.8152
0.7488 1.0870 50 0.7795 {'accuracy': 0.8152173913043478} 0.7322 0.6646 0.8152
0.6911 1.6304 75 0.7066 {'accuracy': 0.8152173913043478} 0.7322 0.6646 0.8152
0.8113 2.1739 100 0.8012 {'accuracy': 0.8152173913043478} 0.7322 0.6646 0.8152
0.634 2.7174 125 0.7801 {'accuracy': 0.8152173913043478} 0.7322 0.6646 0.8152
0.6503 3.2609 150 0.7712 {'accuracy': 0.8152173913043478} 0.7322 0.6646 0.8152
0.7523 3.8043 175 0.7078 {'accuracy': 0.8152173913043478} 0.7322 0.6646 0.8152
0.5493 4.3478 200 0.7484 {'accuracy': 0.8152173913043478} 0.7322 0.6646 0.8152
0.7253 4.8913 225 0.7341 {'accuracy': 0.8152173913043478} 0.7322 0.6646 0.8152

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.1+cu121
  • Datasets 3.0.1
  • Tokenizers 0.19.1
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Model tree for Wiam/wav2vec2-large-xlsr-53-english-finetuned-babycry-v3

Base model

jonatasgrosman/wav2vec2-large-xlsr-53-english
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Evaluation results

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