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wav2vec2-base-finetuned-sentiment-mesd-v2

This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.7213
  • Accuracy: 0.3923

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 1.25e-05
  • train_batch_size: 64
  • eval_batch_size: 40
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 256
  • 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 Validation Loss Accuracy
No log 0.86 3 1.7961 0.1462
1.9685 1.86 6 1.7932 0.1692
1.9685 2.86 9 1.7891 0.2
2.1386 3.86 12 1.7820 0.2923
1.9492 4.86 15 1.7750 0.2923
1.9492 5.86 18 1.7684 0.2846
2.1143 6.86 21 1.7624 0.3231
2.1143 7.86 24 1.7561 0.3308
2.0945 8.86 27 1.7500 0.3462
1.9121 9.86 30 1.7443 0.3385
1.9121 10.86 33 1.7386 0.3231
2.0682 11.86 36 1.7328 0.3231
2.0682 12.86 39 1.7272 0.3769
2.0527 13.86 42 1.7213 0.3923
1.8705 14.86 45 1.7154 0.3846
1.8705 15.86 48 1.7112 0.3846
2.0263 16.86 51 1.7082 0.3769
2.0263 17.86 54 1.7044 0.3846
2.0136 18.86 57 1.7021 0.3846
1.8429 19.86 60 1.7013 0.3846

Framework versions

  • Transformers 4.17.0
  • Pytorch 1.10.0+cu111
  • Datasets 2.0.0
  • Tokenizers 0.11.6
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