README.md

metadata

license: apache-2.0
base_model: Abdalla312/wav2vec2-base-finetuned-ks
tags:
  - generated_from_trainer
datasets:
  - audiofolder
metrics:
  - accuracy
model-index:
  - name: wav2vec2-base-finetuned-ks
    results:
      - task:
          name: Audio Classification
          type: audio-classification
        dataset:
          name: audiofolder
          type: audiofolder
          config: default
          split: validation
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9999221365724519

wav2vec2-base-finetuned-ks

This model is a fine-tuned version of Abdalla312/wav2vec2-base-finetuned-ks on the audiofolder dataset. It achieves the following results on the evaluation set:

• Loss: 0.0003
• Accuracy: 0.9999

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: 16
• eval_batch_size: 16
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 64
• 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
0.0069	1.0	511	0.0376	0.9914
0.0	2.0	1023	0.0003	0.9999
0.0	3.0	1533	0.0006	0.9999

Framework versions

• Transformers 4.39.3
• Pytorch 2.1.2
• Datasets 2.18.0
• Tokenizers 0.15.2