Edit model card

AST_speechcommandsV2_final

This model is a fine-tuned version of MIT/ast-finetuned-audioset-10-10-0.4593 on the speech_commands dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4825
  • Accuracy: 0.8890

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: 72
  • eval_batch_size: 72
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 288
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.3557 1.0 294 0.7017 0.8354
0.1948 2.0 589 0.6838 0.8397
0.1219 3.0 884 0.5752 0.8699
0.0704 4.0 1179 0.5554 0.8675
0.0404 5.0 1473 0.5437 0.8663
0.0136 6.0 1768 0.5247 0.8759
0.0072 7.0 2063 0.5235 0.8759
0.0026 8.0 2358 0.5035 0.8859
0.0007 9.0 2652 0.4800 0.8896
0.0005 9.97 2940 0.4825 0.8890

Framework versions

  • Transformers 4.35.0
  • Pytorch 2.1.0+cu121
  • Datasets 2.14.6
  • Tokenizers 0.14.1
Downloads last month
2
Safetensors
Model size
86.2M params
Tensor type
F32
·

Finetuned from

Dataset used to train moonseok/AST_speechcommandsV2_final

Evaluation results