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deberta-v3-base-zalo-v1

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metadata
license: mit
base_model: microsoft/deberta-v3-base
tags:
  - generated_from_trainer
model-index:
  - name: deberta-v3-base-zalo-v1
    results: []

deberta-v3-base-zalo-v1

This model is a fine-tuned version of microsoft/deberta-v3-base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.3848
  • Map@3: 0.6788

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: 2e-05
  • train_batch_size: 8
  • eval_batch_size: 2
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss Map@3
1.3875 0.02 25 1.3864 0.4245
1.388 0.04 50 1.3863 0.4449
1.388 0.06 75 1.3863 0.4549
1.3862 0.08 100 1.3863 0.4674
1.3867 0.1 125 1.3862 0.5061
1.3859 0.13 150 1.3861 0.5347
1.3871 0.15 175 1.3860 0.5556
1.3851 0.17 200 1.3860 0.5764
1.3865 0.19 225 1.3859 0.5751
1.3853 0.21 250 1.3859 0.5864
1.3863 0.23 275 1.3858 0.6128
1.3858 0.25 300 1.3857 0.6176
1.3875 0.27 325 1.3857 0.6350
1.3863 0.29 350 1.3856 0.6432
1.3858 0.31 375 1.3856 0.6502
1.3861 0.34 400 1.3855 0.6589
1.3867 0.36 425 1.3855 0.6593
1.387 0.38 450 1.3854 0.6693
1.3853 0.4 475 1.3854 0.6615
1.3876 0.42 500 1.3853 0.6753
1.386 0.44 525 1.3853 0.6788
1.3844 0.46 550 1.3852 0.6784
1.386 0.48 575 1.3852 0.6845
1.3861 0.5 600 1.3852 0.6753
1.3872 0.52 625 1.3851 0.6788
1.3864 0.55 650 1.3851 0.6827
1.3857 0.57 675 1.3850 0.6918
1.385 0.59 700 1.3850 0.6823
1.3851 0.61 725 1.3850 0.6714
1.3862 0.63 750 1.3850 0.6784
1.3851 0.65 775 1.3849 0.6836
1.3839 0.67 800 1.3849 0.6775
1.3859 0.69 825 1.3849 0.6823
1.3847 0.71 850 1.3848 0.6910
1.3848 0.73 875 1.3848 0.6853
1.3859 0.75 900 1.3848 0.6827
1.3865 0.78 925 1.3848 0.6866
1.3857 0.8 950 1.3848 0.6810
1.3861 0.82 975 1.3848 0.6845
1.3864 0.84 1000 1.3848 0.6840
1.3851 0.86 1025 1.3848 0.6806
1.3846 0.88 1050 1.3848 0.6823
1.3866 0.9 1075 1.3848 0.6845
1.3857 0.92 1100 1.3847 0.6814
1.3858 0.94 1125 1.3847 0.6892
1.3856 0.96 1150 1.3847 0.6810
1.3853 0.99 1175 1.3848 0.6788

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu118
  • Datasets 2.15.0
  • Tokenizers 0.15.0