wav2vec2-base-960h / README.md
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metadata
license: apache-2.0
base_model: facebook/wav2vec2-base-960h
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: wav2vec2-base-960h
    results: []

wav2vec2-base-960h

This model is a fine-tuned version of facebook/wav2vec2-base-960h on an unknown dataset. It achieves the following results on the evaluation set:

  • Accuracy: 0.8830
  • Loss: 0.4259

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: 5
  • eval_batch_size: 5
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 20
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 20

Training results

Training Loss Epoch Step Accuracy Validation Loss
0.7016 1.0 125 0.7933 0.6439
0.7121 2.0 250 0.5962 0.7870
0.4491 3.0 375 0.8782 0.4561
0.4606 4.0 500 0.8526 0.5664
0.425 5.0 625 0.8718 0.4652
0.4852 6.0 750 0.8397 0.5111
0.3023 7.0 875 0.8766 0.4319
0.2247 8.0 1000 0.8654 0.5093
0.4269 9.0 1125 0.8926 0.4148
0.348 10.0 1250 0.8846 0.3861
0.5049 11.0 1375 0.8814 0.4141
0.2305 12.0 1500 0.8878 0.3804
0.2839 13.0 1625 0.8990 0.3682
0.1739 14.0 1750 0.9022 0.3917
0.2808 15.0 1875 0.8926 0.4303
0.2306 16.0 2000 0.9006 0.3951
0.2766 17.0 2125 0.8974 0.4003
0.1212 18.0 2250 0.8910 0.3999
0.2822 19.0 2375 0.8766 0.4390
0.1391 20.0 2500 0.8830 0.4259

Framework versions

  • Transformers 4.40.1
  • Pytorch 2.2.1+cu121
  • Datasets 2.19.0
  • Tokenizers 0.19.1