This model is a fine-tuned version of facebook/wav2vec2-base-960h on a merged dataset of RAVDESS, CREMA, SAVEE, and TESS.
It achieves the following results on the evaluation set:
eval_accuracy: 0.7480
eval_loss: 0.7940
eval_weighted_f1: 0.7438
eval_micro_f1: 0.7480
eval_macro_f1: 0.7559
eval_weighted_recall: 0.7480
eval_micro_recall: 0.7480
eval_macro_recall: 0.7622
eval_weighted_precision: 0.7518
eval_micro_precision: 0.7480
eval_macro_precision: 0.7609
eval_runtime: 82.1913
eval_samples_per_second: 29.602
eval_steps_per_second: 0.937
epoch: 14.0
step: 1078
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-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
