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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: mind_audio_classification_model
    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: 0.017699115044247787

mind_audio_classification_model

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: 2.6543
  • Accuracy: 0.0177

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 0.8 3 2.6352 0.1150
No log 1.87 7 2.6403 0.0619
2.6383 2.93 11 2.6470 0.0442
2.6383 4.0 15 2.6542 0.0177
2.6383 4.8 18 2.6569 0.0177
2.6209 5.87 22 2.6551 0.0177
2.6209 6.93 26 2.6536 0.0177
2.6143 8.0 30 2.6543 0.0177

Framework versions

  • Transformers 4.32.1
  • Pytorch 2.0.0
  • Datasets 2.1.0
  • Tokenizers 0.13.3