my_custom2_model / README.md
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metadata
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
  - generated_from_trainer
datasets:
  - audiofolder
metrics:
  - accuracy
model-index:
  - name: my_custom2_model
    results:
      - task:
          name: Audio Classification
          type: audio-classification
        dataset:
          name: audiofolder
          type: audiofolder
          config: default
          split: train
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9166666666666666

my_custom2_model

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

  • Loss: 0.4030
  • Accuracy: 0.9167

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: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 8
  • optimizer: Use OptimizerNames.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: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.1798 1.0 6 0.4439 0.75
0.2051 2.0 12 0.5505 0.5833
0.1612 3.0 18 0.1884 0.9167
0.2032 4.0 24 0.2759 0.9167
0.1803 5.0 30 0.5196 0.8333
0.0478 6.0 36 0.3214 0.9167
0.1159 7.0 42 0.3311 0.9167
0.031 8.0 48 0.6261 0.8333
0.0263 9.0 54 0.3536 0.9167
0.2505 10.0 60 0.3637 0.9167
0.018 11.0 66 0.3721 0.9167
0.0167 12.0 72 0.6487 0.8333
0.0154 13.0 78 0.7422 0.8333
0.0144 14.0 84 0.7221 0.8333
0.0129 15.0 90 0.5876 0.8333
0.0123 16.0 96 0.4041 0.9167
0.0118 17.0 102 0.4000 0.9167
0.0115 18.0 108 0.4015 0.9167
0.0112 19.0 114 0.4025 0.9167
0.011 20.0 120 0.4030 0.9167

Framework versions

  • Transformers 4.50.3
  • Pytorch 2.6.0+cu124
  • Datasets 3.5.0
  • Tokenizers 0.21.1