w2v2-ks-jpqd-lr1e-4

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

  • Loss: 0.1228
  • Accuracy: 0.9695

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: 0.0001
  • train_batch_size: 32
  • eval_batch_size: 64
  • seed: 0
  • 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: 15.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
2.5357 1.0 399 2.7821 0.6209
2.7107 2.0 798 2.7331 0.6209
2.671 3.0 1197 2.7330 0.6209
14.208 4.0 1596 14.2660 0.7139
21.0916 5.0 1995 21.0315 0.8104
24.4471 6.0 2394 24.2357 0.9073
25.366 7.0 2793 25.0893 0.9273
25.1369 8.0 3192 24.8976 0.9394
0.4678 9.0 3591 0.2528 0.9435
0.3576 10.0 3990 0.1873 0.9613
0.3622 11.0 4389 0.1583 0.9645
0.2796 12.0 4788 0.1419 0.9666
0.3157 13.0 5187 0.1327 0.9693
0.2997 14.0 5586 0.1263 0.9694
0.2667 15.0 5985 0.1228 0.9695

Framework versions

  • Transformers 4.26.0
  • Pytorch 1.13.1+cu116
  • Datasets 2.8.0
  • Tokenizers 0.13.2
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Dataset used to train yujiepan/internal.wav2vec2-base-superb-ks-int8-structured83