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contract-ner-model-da

This model is a fine-tuned version of xlm-roberta-base on a custom contracts dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0026
  • Micro F1: 0.9297

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 2e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 919
  • num_epochs: 500

Training results

Training Loss Epoch Step Validation Loss Micro F1
0.8971 0.24 200 0.0205 0.0
0.0173 0.48 400 0.0100 0.2921
0.0092 0.73 600 0.0065 0.7147
0.0063 0.97 800 0.0046 0.8332
0.0047 1.21 1000 0.0047 0.8459
0.0042 1.45 1200 0.0039 0.8694
0.0037 1.69 1400 0.0035 0.8888
0.0032 1.93 1600 0.0035 0.8840
0.0025 2.18 1800 0.0029 0.8943
0.0023 2.42 2000 0.0024 0.9104
0.0023 2.66 2200 0.0032 0.8808
0.0021 2.9 2400 0.0022 0.9338
0.0018 3.14 2600 0.0020 0.9315
0.0015 3.39 2800 0.0026 0.9297

Framework versions

  • Transformers 4.11.3
  • Pytorch 1.8.1+cu101
  • Datasets 1.12.1
  • Tokenizers 0.10.3
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