wav2vec2-base-960h_SER_merged_dataset

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
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 15

Framework versions

  • Transformers 4.47.0
  • Pytorch 2.5.1+cu121
  • Datasets 3.3.1
  • Tokenizers 0.21.0
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