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metadata
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: wav2vec2-base-finetuned-organ
    results: []

wav2vec2-base-finetuned-organ

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

  • Loss: 1.2973
  • Accuracy: 0.8182

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: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 50
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.0652 1.0 6 0.0202 1.0
0.0226 2.0 12 0.0171 1.0
0.1719 3.0 18 0.5006 0.9091
0.1115 4.0 24 1.4275 0.7273
0.191 5.0 30 0.3866 0.9091
0.4063 6.0 36 1.6167 0.7273
0.6557 7.0 42 2.5850 0.5455
0.7413 8.0 48 1.7765 0.5455
0.8188 9.0 54 2.1469 0.5455
1.168 10.0 60 1.0001 0.8182
0.9951 11.0 66 1.0984 0.8182
0.7365 12.0 72 1.6653 0.5455
0.5536 13.0 78 1.2873 0.7273
0.8315 14.0 84 0.2661 0.9091
0.3605 15.0 90 0.2670 0.9091
0.6238 16.0 96 0.5140 0.8182
0.3698 17.0 102 0.5254 0.8182
0.2818 18.0 108 1.1506 0.6364
0.4245 19.0 114 1.2583 0.6364
0.6101 20.0 120 0.9249 0.7273
0.2197 21.0 126 1.1442 0.7273
0.2161 22.0 132 1.6102 0.6364
0.6048 23.0 138 1.3656 0.7273
0.1764 24.0 144 1.4459 0.7273
0.1602 25.0 150 1.4824 0.7273
0.185 26.0 156 1.5401 0.7273
0.0679 27.0 162 1.6073 0.7273
0.1278 28.0 168 1.0710 0.8182
0.1546 29.0 174 0.5503 0.9091
0.2121 30.0 180 0.5570 0.9091
0.0087 31.0 186 0.5756 0.9091
0.2233 32.0 192 1.1581 0.8182
0.0088 33.0 198 1.1720 0.8182
0.1851 34.0 204 1.5192 0.6364
0.0098 35.0 210 1.7753 0.7273
0.008 36.0 216 1.8136 0.7273
0.0648 37.0 222 1.8277 0.7273
0.1351 38.0 228 1.8239 0.7273
0.1287 39.0 234 1.7748 0.7273
0.0712 40.0 240 1.6251 0.7273
0.0503 41.0 246 1.2516 0.8182
0.1273 42.0 252 1.2622 0.8182
0.0859 43.0 258 1.2601 0.8182
0.073 44.0 264 1.2624 0.8182
0.2027 45.0 270 1.2639 0.8182
0.0477 46.0 276 1.2667 0.8182
0.1111 47.0 282 1.2688 0.8182
0.072 48.0 288 1.2689 0.8182
0.0615 49.0 294 1.2726 0.8182
0.0049 50.0 300 1.2973 0.8182

Framework versions

  • Transformers 4.42.3
  • Pytorch 2.3.1+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1