README.md

metadata

tags:
  - generated_from_trainer
datasets:
  - superb
metrics:
  - accuracy
model-index:
  - name: wav2vec2-base-finetuned-ks-balanced3
    results:
      - task:
          name: Audio Classification
          type: audio-classification
        dataset:
          name: superb
          type: superb
          config: ks
          split: validation
          args: ks
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9058546631362165

wav2vec2-base-finetuned-ks-balanced3

This model was trained from scratch on the superb dataset. It achieves the following results on the evaluation set:

• Loss: 0.3610
• Accuracy: 0.9059

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: 64
• eval_batch_size: 64
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 256
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.1553	0.99	79	0.3610	0.9059
0.1672	1.99	159	0.5316	0.8569
0.1428	3.0	239	0.4606	0.8670
0.1477	4.0	319	0.4181	0.8825
0.1226	4.95	395	0.4867	0.8711

Framework versions

• Transformers 4.33.3
• Pytorch 2.0.1+cu117
• Datasets 2.14.5
• Tokenizers 0.13.3