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metadata
license: apache-2.0
base_model: facebook/wav2vec2-large
tags:
  - generated_from_trainer
datasets:
  - audiofolder
metrics:
  - accuracy
model-index:
  - name: facebook_wav2vec2-large_October_03_2023_05h34PM
    results:
      - task:
          name: Audio Classification
          type: audio-classification
        dataset:
          name: audiofolder
          type: audiofolder
          config: default
          split: validation
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9743347801471975

facebook_wav2vec2-large_October_03_2023_05h34PM

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

  • Loss: 0.1318
  • Accuracy: 0.9743

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: 64
  • eval_batch_size: 64
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 256
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 15

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.4214 1.0 121 0.3650 0.7932
0.1959 2.0 242 0.2588 0.8960
0.1365 3.0 363 0.0732 0.9713
0.1003 4.0 484 0.0849 0.9719
0.0806 5.0 605 0.2170 0.9381
0.0588 6.0 726 0.0738 0.9760
0.0472 7.0 847 0.2083 0.9409
0.0505 8.0 968 0.1020 0.9760
0.0427 9.0 1089 0.0626 0.9809
0.0285 10.0 1210 0.1062 0.9732
0.0286 11.0 1331 0.1068 0.9738
0.0231 12.0 1452 0.1137 0.9755
0.0232 13.0 1573 0.0783 0.9815
0.0158 14.0 1694 0.1138 0.9755
0.0164 15.0 1815 0.1318 0.9743

Framework versions

  • Transformers 4.33.3
  • Pytorch 2.2.0.dev20230927+cu121
  • Datasets 2.14.5
  • Tokenizers 0.13.3