nicolauduran45 / affilgood-span-v2

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Total runs: 91
24-hour runs: 0
7-day runs: 0
30-day runs: 0
Model's Last Updated: October 31 2024
token-classification

Introduction of affilgood-span-v2

Model Details of affilgood-span-v2

affilgood-span-v2

This model is a fine-tuned version of SIRIS-Lab/affilgood-affilroberta on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2360
  • Precision: 0.8321
  • Recall: 0.8934
  • F1: 0.8617
  • Accuracy: 0.9612
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: 32
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 15
Training results
Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 1.0 93 0.1532 0.7861 0.8333 0.8090 0.9567
No log 2.0 186 0.1135 0.8404 0.8634 0.8518 0.9610
No log 3.0 279 0.1021 0.8333 0.9016 0.8661 0.9682
No log 4.0 372 0.1183 0.8182 0.8852 0.8504 0.9673
No log 5.0 465 0.1377 0.8564 0.8962 0.8758 0.9685
0.0987 6.0 558 0.1296 0.8575 0.9044 0.8803 0.9682
0.0987 7.0 651 0.1568 0.8583 0.8934 0.8755 0.9685
0.0987 8.0 744 0.2092 0.8575 0.8880 0.8725 0.9649
0.0987 9.0 837 0.2360 0.8321 0.8934 0.8617 0.9612
Framework versions
  • Transformers 4.44.2
  • Pytorch 2.5.0+cu121
  • Datasets 3.0.2
  • Tokenizers 0.19.1

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