data2vec

82.1% passed tests (321 passed / 70 failed).

Tests overview

Topic	Passed Tests
Correctness consistency	48.8%
Correctness distribution	66.7%
Correctness regression	66.7%
Correctness speaker average	100.0%
Correctness speaker ranking	100.0%
Fairness accent	96.8%
Fairness language	83.3%
Fairness linguistic sentiment	87.5%
Fairness pitch	93.3%
Fairness sex	90.6%
Robustness background noise	54.2%
Robustness low quality phone	75.0%
Robustness recording condition	50.0%
Robustness simulated recording condition	16.7%
Robustness small changes	90.0%
Robustness spectral tilt	62.5%

Model parameters

Entry	Value
model	{‘architecture’: ‘data2vec’, ‘basemodel’: ‘facebook/data2vec-audio-large’, ‘n_layers’: 24}
data	[‘msppodcast’]
sampling_rate	16000
quantization	False

Model information

Entry	Value
Author	aderington
Date	2024-10-02
Name	onnx
Subgroup	ser.adv.data2vec
Version	1.0.0
Data	{‘train’: {‘msppodcast’: {‘version’: ‘2.6.1’, ‘tables’: [‘emotion.dimensions.train.gold_standard’]}}, ‘dev’: {‘msppodcast’: {‘version’: ‘2.6.1’, ‘tables’: [‘emotion.dimensions.dev.gold_standard’]}}, ‘config’: {‘datasets’: {‘msppodcast-train-dev’: {‘name’: ‘msppodcast’, ‘version’: ‘2.6.1’, ‘tables’: {‘train’: ‘emotion.dimensions.train.gold_standard’, ‘dev’: ‘emotion.dimensions.dev.gold_standard’}}, ‘msppodcast-test-1’: {‘name’: ‘msppodcast’, ‘version’: ‘2.6.1’, ‘tables’: {‘test’: ‘emotion.dimensions.test-1.gold_standard’}}, ‘msppodcast-test-2’: {‘name’: ‘msppodcast’, ‘version’: ‘2.6.1’, ‘tables’: {‘test’: ‘emotion.dimensions.test-2.gold_standard’}}}}}
Model	{‘basemodel’: ‘facebook/data2vec-audio-large’, ‘n_layers’: 24, ‘gradient_accum_steps’: 2, ‘use_fp16’: True, ‘per_device_train_batch_size’: 4, ‘per_device_eval_batch_size’: 4, ‘learning_rate’: 5e-05, ‘n_epochs’: 5, ‘eval_steps’: 100, ‘save_steps’: 100, ‘min_length_train’: 0.5, ‘max_length_train’: 8, ‘metric_for_eval’: ‘combined’, ‘main_metrics’: {‘arousal’: ‘CCC’, ‘dominance’: ‘CCC’, ‘valence’: ‘CCC’}, ‘sampling_rate’: 16000, ‘seed’: 1, ‘tasks’: [‘arousal’, ‘dominance’, ‘valence’], ‘labels’: None, ‘task2problemtype’: {‘arousal’: ‘regression’, ‘dominance’: ‘regression’, ‘valence’: ‘regression’}, ‘task2heads’: {‘arousal’: 0, ‘dominance’: 0, ‘valence’: 0}, ‘task2postprocessing’: {‘arousal’: None, ‘dominance’: None, ‘valence’: None}, ‘task2lossweight’: {‘arousal’: 1, ‘dominance’: 1, ‘valence’: 1}}