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PhobertLexicalMeta-v2

This model is a fine-tuned version of gechim/metadata-cls-no-gov-8k-v3 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3926
  • Accuracy: 0.9062
  • F1: 0.8781

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: 64
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
No log 0.8772 100 0.2699 0.9080 0.8801
0.1564 1.7544 200 0.2984 0.9011 0.8723
0.073 2.6316 300 0.3218 0.8987 0.8705
0.0502 3.5088 400 0.3472 0.8927 0.8641
0.0326 4.3860 500 0.3627 0.8941 0.8635
0.0285 5.2632 600 0.3752 0.8964 0.8685
0.0179 6.1404 700 0.3666 0.9025 0.8734
0.0156 7.0175 800 0.3759 0.9043 0.8748
0.0156 7.8947 900 0.3830 0.9080 0.8788
0.011 8.7719 1000 0.3917 0.9039 0.8746
0.0092 9.6491 1100 0.3926 0.9062 0.8781

Framework versions

  • Transformers 4.43.3
  • Pytorch 2.1.2
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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