gary109's picture
update model card README.md
1f1d630
metadata
license: apache-2.0
tags:
  - audio-classification
  - generated_from_trainer
datasets:
  - mir_st500
metrics:
  - accuracy
model-index:
  - name: wav2vec2-base-mirst500-ac
    results: []

wav2vec2-base-mirst500-ac

This model is a fine-tuned version of facebook/wav2vec2-base on the /workspace/datasets/datasets/MIR_ST500/MIR_ST500.py dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7566
  • Accuracy: 0.7570

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: 16
  • eval_batch_size: 1
  • seed: 0
  • distributed_type: multi-GPU
  • num_devices: 2
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 128
  • total_eval_batch_size: 2
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 15.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.3718 1.0 1304 1.4422 0.4255
1.1285 2.0 2608 1.1061 0.5869
1.0275 3.0 3912 0.8825 0.6724
0.9982 4.0 5216 0.9181 0.6713
0.9482 5.0 6520 0.8717 0.6971
0.8687 6.0 7824 0.8041 0.7164
0.8841 7.0 9128 0.8869 0.7034
0.8094 8.0 10432 0.8216 0.7172
0.7733 9.0 11736 0.8018 0.7298
0.7892 10.0 13040 0.7517 0.7426
0.8736 11.0 14344 0.7482 0.7482
0.7035 12.0 15648 0.7730 0.7488
0.7361 13.0 16952 0.7677 0.7510
0.7808 14.0 18256 0.7765 0.7512
0.7359 15.0 19560 0.7566 0.7570

Framework versions

  • Transformers 4.18.0
  • Pytorch 1.9.1+cu102
  • Datasets 2.0.0
  • Tokenizers 0.11.6