metadata

license: apache-2.0
base_model: anton-l/distilhubert-ft-keyword-spotting
tags:
  - generated_from_trainer
datasets:
  - audiofolder
metrics:
  - accuracy
model-index:
  - name: distilhubert-ft-keyword-spotting-finetuned-ks-ob
    results:
      - task:
          name: Audio Classification
          type: audio-classification
        dataset:
          name: audiofolder
          type: audiofolder
          config: default
          split: train
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9850014526438118

distilhubert-ft-keyword-spotting-finetuned-ks-ob

This model is a fine-tuned version of anton-l/distilhubert-ft-keyword-spotting on the audiofolder dataset. It achieves the following results on the evaluation set:

Loss: 0.0459
Accuracy: 0.9850

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: 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
0.1536	1.0	215	0.1282	0.9606
0.0809	2.0	430	0.0752	0.9763
0.0839	3.0	645	0.0638	0.9783
0.0536	4.0	861	0.0588	0.9794
0.0412	4.99	1075	0.0459	0.9850

Framework versions

Transformers 4.37.2
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.1