metadata

library_name: transformers
license: apache-2.0
base_model: imrajeshkr/distilhubert-finetuned-speech_commands
tags:
  - generated_from_trainer
datasets:
  - audiofolder
metrics:
  - f1
model-index:
  - name: distilhubert-finetuned-speech_commands-finetuned-gtzan
    results:
      - task:
          name: Audio Classification
          type: audio-classification
        dataset:
          name: audiofolder
          type: audiofolder
          config: default
          split: validation
          args: default
        metrics:
          - name: F1
            type: f1
            value: 0.9799704307080909

distilhubert-finetuned-speech_commands-finetuned-gtzan

This model is a fine-tuned version of imrajeshkr/distilhubert-finetuned-speech_commands on the audiofolder dataset. It achieves the following results on the evaluation set:

Loss: 0.0751
F1: 0.9800

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: 5e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Use 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: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	F1
0.2364	1.0	1216	0.2190	0.9311
0.1287	2.0	2432	0.1014	0.9678
0.0445	3.0	3648	0.0743	0.9778
0.0037	4.0	4864	0.0785	0.9773
0.0087	5.0	6080	0.0751	0.9800

Framework versions

Transformers 4.47.1
Pytorch 2.2.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0