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wav2vec2-base

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

wav2vec2-base

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: 0.5735
  • Accuracy: 0.8913

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: 0.0003
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • 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: 50

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 0.92 3 2.7459 0.1304
No log 1.85 6 2.6837 0.1087
No log 2.77 9 2.6583 0.1087
2.6599 4.0 13 2.6553 0.1087
2.6599 4.92 16 2.5628 0.1522
2.6599 5.85 19 2.4286 0.1739
2.3457 6.77 22 2.4705 0.1522
2.3457 8.0 26 2.2801 0.1522
2.3457 8.92 29 2.2110 0.2391
2.1136 9.85 32 2.1101 0.2391
2.1136 10.77 35 2.0434 0.3478
2.1136 12.0 39 2.2015 0.2609
1.8271 12.92 42 1.8463 0.2826
1.8271 13.85 45 1.8144 0.2391
1.8271 14.77 48 1.6712 0.2391
1.6517 16.0 52 1.6885 0.4348
1.6517 16.92 55 1.7268 0.4565
1.6517 17.85 58 1.5564 0.5435
1.5123 18.77 61 1.4261 0.5435
1.5123 20.0 65 1.2945 0.6739
1.5123 20.92 68 1.2329 0.6957
1.2441 21.85 71 1.1841 0.6957
1.2441 22.77 74 1.1297 0.7174
1.2441 24.0 78 1.0477 0.7826
1.0647 24.92 81 1.0039 0.7174
1.0647 25.85 84 0.9795 0.7174
1.0647 26.77 87 0.9619 0.7609
0.9374 28.0 91 0.8940 0.8043
0.9374 28.92 94 0.8675 0.8043
0.9374 29.85 97 0.8516 0.8043
0.7902 30.77 100 0.8203 0.8261
0.7902 32.0 104 0.7963 0.7609
0.7902 32.92 107 0.7329 0.8478
0.6959 33.85 110 0.7382 0.8043
0.6959 34.77 113 0.7205 0.8261
0.6959 36.0 117 0.6996 0.8043
0.6694 36.92 120 0.6949 0.8696
0.6694 37.85 123 0.7009 0.7826
0.6694 38.77 126 0.6502 0.8261
0.6226 40.0 130 0.5835 0.8478
0.6226 40.92 133 0.5735 0.8913
0.6226 41.85 136 0.5651 0.8913
0.6226 42.77 139 0.5624 0.8913
0.5746 44.0 143 0.5565 0.8913
0.5746 44.92 146 0.5476 0.8913
0.5746 45.85 149 0.5439 0.8913
0.5238 46.15 150 0.5435 0.8913

Framework versions

  • Transformers 4.37.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.1