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End of training
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metadata
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
  - generated_from_trainer
datasets:
  - speech_commands
metrics:
  - accuracy
model-index:
  - name: wav2vec2-base-finetuned-ks
    results:
      - task:
          name: Audio Classification
          type: audio-classification
        dataset:
          name: speech_commands
          type: speech_commands
          config: v0.02
          split: validation
          args: v0.02
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9632338208775797

wav2vec2-base-finetuned-ks

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

  • Loss: 1.5562
  • Accuracy: 0.9632

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: 256
  • eval_batch_size: 256
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 1024
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss Accuracy
2.5366 1.0 83 2.2424 0.8575
1.963 2.0 166 1.6987 0.9537
1.7887 3.0 249 1.5562 0.9632

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1