metadata

library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
  - generated_from_trainer
datasets:
  - speech_commands
metrics:
  - accuracy
model-index:
  - name: Speech_Commands_Model
    results:
      - task:
          name: Audio Classification
          type: audio-classification
        dataset:
          name: speech_commands
          type: speech_commands
          config: v0.01
          split: train
          args: v0.01
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9755357667090714

Speech_Commands_Model

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: 0.1543
Accuracy: 0.9755

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 OptimizerNames.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: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.4629	1.0	320	0.2712	0.9683
0.3143	2.0	640	0.1806	0.9717
0.2891	3.0	960	0.1543	0.9755

Framework versions

Transformers 4.52.4
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.2