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metadata
license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: wav2vec2-conformer-rel-pos-large-960h-ft-intent-classification-ori
    results: []

wav2vec2-conformer-rel-pos-large-960h-ft-intent-classification-ori

This model is a fine-tuned version of facebook/wav2vec2-conformer-rel-pos-large-960h-ft on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.2518
  • Accuracy: 0.5833

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: 1
  • eval_batch_size: 1
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 4
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 45

Training results

Training Loss Epoch Step Validation Loss Accuracy
2.2018 1.0 28 2.1963 0.125
2.1871 2.0 56 2.1715 0.3333
2.1499 3.0 84 2.1349 0.3333
2.1236 4.0 112 2.0749 0.3333
2.0814 5.0 140 2.0232 0.3333
2.0905 6.0 168 1.9028 0.375
1.9167 7.0 196 1.8469 0.3958
1.7048 8.0 224 1.6481 0.4583
1.4723 9.0 252 1.5350 0.4583
1.5265 10.0 280 1.4526 0.5
1.2621 11.0 308 1.4451 0.4583
1.5083 12.0 336 1.3296 0.4792
1.1857 13.0 364 1.2983 0.4792
1.3449 14.0 392 1.3026 0.4792
1.2061 15.0 420 1.3181 0.4792
1.2544 16.0 448 1.2603 0.4792
1.0731 17.0 476 1.2607 0.4792
0.8836 18.0 504 1.2644 0.4792
1.0917 19.0 532 1.2345 0.4792
1.0786 20.0 560 1.2791 0.4792
1.1616 21.0 588 1.2238 0.4792
1.0614 22.0 616 1.2305 0.4583
0.9617 23.0 644 1.2315 0.4792
0.9652 24.0 672 1.2931 0.4792
0.9042 25.0 700 1.1246 0.5
1.0865 26.0 728 1.1490 0.4792
0.9653 27.0 756 1.1713 0.5
0.858 28.0 784 1.1726 0.5208
0.8364 29.0 812 1.2142 0.5
0.6798 30.0 840 1.2163 0.5208
0.9284 31.0 868 1.1398 0.4792
0.7383 32.0 896 1.2418 0.5208
0.651 33.0 924 1.1734 0.5
0.7416 34.0 952 1.2285 0.5
0.6287 35.0 980 1.1467 0.5833
0.6806 36.0 1008 1.1589 0.5625
0.6148 37.0 1036 1.1373 0.5833
0.7174 38.0 1064 1.2118 0.5625
0.6056 39.0 1092 1.2205 0.5833
0.7041 40.0 1120 1.2408 0.5833
0.631 41.0 1148 1.2350 0.5833
0.6028 42.0 1176 1.2787 0.5833
0.5942 43.0 1204 1.2463 0.5833
0.5441 44.0 1232 1.2496 0.5833
0.5042 45.0 1260 1.2518 0.5833

Framework versions

  • Transformers 4.20.1
  • Pytorch 1.11.0
  • Datasets 2.1.0
  • Tokenizers 0.12.1