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Arousal Only Train
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metadata
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: Arousal-wav2vec2-base-EMOPIA
    results: []

Arousal-wav2vec2-base-EMOPIA

This model is a fine-tuned version of facebook/wav2vec2-base on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4207
  • Accuracy: 0.9014

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: 1e-06
  • train_batch_size: 1
  • eval_batch_size: 1
  • seed: 42
  • gradient_accumulation_steps: 3
  • total_train_batch_size: 3
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 1000
  • num_epochs: 15
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.6871 1.0 269 0.6601 0.6761
0.6071 2.0 538 0.5375 0.8451
0.4312 3.0 807 0.3544 0.8873
0.306 4.0 1076 0.3780 0.8592
0.3052 5.0 1345 0.4133 0.8873
0.3099 6.0 1614 0.4112 0.8873
0.2965 7.0 1883 0.4241 0.8873
0.2954 8.0 2152 0.4381 0.8873
0.2905 9.0 2421 0.4294 0.9014
0.2868 10.0 2690 0.4208 0.9014
0.284 11.0 2959 0.4077 0.9014
0.2666 12.0 3228 0.4149 0.9014
0.2697 13.0 3497 0.4108 0.9014
0.2622 14.0 3766 0.4187 0.9014
0.2648 15.0 4035 0.4207 0.9014

Framework versions

  • Transformers 4.37.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.1