edos-2023-baseline-microsoft-deberta-v3-base-label_vector

This model is a fine-tuned version of microsoft/deberta-v3-base on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.5524
  • F1: 0.3162

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: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 5
  • num_epochs: 12
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss F1
2.1209 1.18 100 1.9990 0.0801
1.7997 2.35 200 1.7293 0.1349
1.5749 3.53 300 1.6080 0.2431
1.3674 4.71 400 1.5411 0.2793
1.2214 5.88 500 1.5285 0.2980
1.0752 7.06 600 1.5165 0.3054
0.9899 8.24 700 1.5210 0.3186
0.8733 9.41 800 1.5385 0.3134
0.8578 10.59 900 1.5524 0.3162

Framework versions

  • Transformers 4.24.0
  • Pytorch 1.12.1+cu113
  • Datasets 2.7.1
  • Tokenizers 0.13.2
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