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add_bert_12_layer_model_complete_training_new_96

This model is a fine-tuned version of gokuls/add_bert_12_layer_model_complete_training_new_48 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 5.4112
  • Accuracy: 0.1893

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: 1e-05
  • train_batch_size: 48
  • eval_batch_size: 48
  • seed: 10
  • distributed_type: multi-GPU
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 10000
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss Accuracy
5.8144 0.08 10000 5.7474 0.1593
5.7889 0.16 20000 5.7204 0.1604
5.6347 0.25 30000 5.6966 0.1623
5.7138 0.33 40000 5.6725 0.1636
5.6769 0.41 50000 5.6518 0.1658
5.6603 0.49 60000 5.6290 0.1686
5.5852 0.57 70000 5.6076 0.1707
5.6607 0.66 80000 5.5906 0.1720
5.5823 0.74 90000 5.5719 0.1739
5.6124 0.82 100000 5.5543 0.1759
5.6478 0.9 110000 5.5358 0.1776
5.4795 0.98 120000 5.5203 0.1787
5.4557 1.07 130000 5.5028 0.1804
5.5585 1.15 140000 5.4923 0.1814
5.6387 1.23 150000 5.4781 0.1825
5.479 1.31 160000 5.4663 0.1833
5.3951 1.39 170000 5.4512 0.1851
5.5062 1.47 180000 5.4411 0.1864
5.4553 1.56 190000 5.4244 0.1881
5.5461 1.64 200000 5.4112 0.1893

Framework versions

  • Transformers 4.30.1
  • Pytorch 1.14.0a0+410ce96
  • Datasets 2.12.0
  • Tokenizers 0.13.3
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