README.md

metadata

library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
  - generated_from_trainer
datasets:
  - speech_commands
metrics:
  - accuracy
  - f1
model-index:
  - name: wav2vec
    results:
      - task:
          name: Audio Classification
          type: audio-classification
        dataset:
          name: speech_commands
          type: speech_commands
          config: v0.01
          split: test
          args: v0.01
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8938656280428432
          - name: F1
            type: f1
            value: 0.8871854520046679

wav2vec

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

• Loss: 0.4992
• Accuracy: 0.8939
• F1: 0.8872

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: 80
• eval_batch_size: 80
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.6895	1.0	639	0.7875	0.8773	0.7995
0.4171	2.0	1278	0.5445	0.8932	0.8675
0.2706	3.0	1917	0.4992	0.8939	0.8872

Framework versions

• Transformers 4.45.1
• Pytorch 2.4.0
• Datasets 3.0.1
• Tokenizers 0.20.0