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metadata
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
  - generated_from_trainer
datasets:
  - minds14
metrics:
  - accuracy
model-index:
  - name: my_awesome_mind_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: 0.061946902654867256

my_awesome_mind_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: 2.6953
  • Accuracy: 0.0619

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: Use 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: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 0.8 3 2.6477 0.0708
No log 1.9333 7 2.6612 0.0619
2.6309 2.8 10 2.6706 0.0708
2.6309 3.9333 14 2.6782 0.0796
2.6309 4.8 17 2.6847 0.0619
2.6133 5.9333 21 2.6933 0.0619
2.6133 6.8 24 2.6951 0.0619
2.6133 7.9333 28 2.6950 0.0619
2.603 8.5333 30 2.6953 0.0619

Framework versions

  • Transformers 4.46.2
  • Pytorch 2.5.1+cu121
  • Datasets 3.1.0
  • Tokenizers 0.20.3