wav2vec-reptiles / README.md
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metadata
license: mit
base_model: facebook/w2v-bert-2.0
tags:
  - generated_from_trainer
model-index:
  - name: wav2vec-reptiles
    results: []

wav2vec-reptiles

This model is a fine-tuned version of facebook/w2v-bert-2.0 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 484.9289
  • Pcc Accuracy: -0.1604
  • Pcc Fluency: -0.1393
  • Pcc Total Score: -0.1591
  • Pcc Content: -0.1544

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: 4
  • eval_batch_size: 6
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 8
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.4
  • num_epochs: 10
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Pcc Accuracy Pcc Fluency Pcc Total Score Pcc Content
3175.5941 1.07 500 2802.1936 -0.2863 -0.2729 -0.3001 -0.2745
1733.457 2.13 1000 2440.8833 -0.2827 -0.2779 -0.2959 -0.2787
1890.6879 3.2 1500 1470.4958 -0.2806 -0.2763 -0.2933 -0.2772
470.8979 4.27 2000 565.3928 -0.2658 -0.2589 -0.2764 -0.2621
881.7893 5.34 2500 501.9731 -0.2331 -0.2204 -0.2394 -0.2285
379.352 6.4 3000 497.4395 -0.2040 -0.1871 -0.2068 -0.1982
378.5915 7.47 3500 491.6927 -0.1783 -0.1590 -0.1789 -0.1726
539.6395 8.54 4000 487.6133 -0.1639 -0.1434 -0.1631 -0.1582
319.019 9.61 4500 484.9289 -0.1604 -0.1393 -0.1591 -0.1544

Framework versions

  • Transformers 4.37.0
  • Pytorch 2.1.2
  • Datasets 2.17.1
  • Tokenizers 0.15.1