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metadata
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
  - generated_from_trainer
datasets:
  - minds14
metrics:
  - accuracy
model-index:
  - name: wav2vec2-base-finetuned-minds-1
    results:
      - task:
          name: Audio Classification
          type: audio-classification
        dataset:
          name: minds14
          type: minds14
          config: en-US
          split: train
          args: en-US
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.7610619469026548

wav2vec2-base-finetuned-minds-1

This model is a fine-tuned version of facebook/wav2vec2-base on the minds14 dataset. It achieves the following results on the evaluation set:

  • Loss: 1.4208
  • Accuracy: 0.7611

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: 5e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 10
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
2.6059 1.0 57 2.5954 0.0973
2.5183 2.0 114 2.5787 0.0973
2.5497 3.0 171 2.5629 0.1416
2.3827 4.0 228 2.5407 0.1858
2.309 5.0 285 2.3023 0.2301
2.0098 6.0 342 2.0528 0.3540
1.797 7.0 399 1.8558 0.4602
1.4416 8.0 456 1.6847 0.5841
1.3491 9.0 513 1.4911 0.6991
1.3468 10.0 570 1.4208 0.7611

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2