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xmod-shared-roberta-base-legal-multi-downstream-build_rr

Token Classification
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xmod
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metadata
library_name: transformers
base_model: MHGanainy/xmod-shared-roberta-base-legal-multi
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: xmod-shared-roberta-base-legal-multi-downstream-build_rr
    results: []

xmod-shared-roberta-base-legal-multi-downstream-build_rr

This model is a fine-tuned version of MHGanainy/xmod-shared-roberta-base-legal-multi on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9259
  • Precision-macro: 0.6337
  • Recall-macro: 0.5884
  • Macro-f1: 0.6021
  • Precision-micro: 0.7895
  • Recall-micro: 0.7895
  • Micro-f1: 0.7895
  • Accuracy: 0.7895

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: 3e-05
  • train_batch_size: 2
  • eval_batch_size: 2
  • seed: 1
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Precision-macro Recall-macro Macro-f1 Precision-micro Recall-micro Micro-f1 Accuracy
No log 1.0 124 0.8663 0.5370 0.4683 0.4780 0.7461 0.7461 0.7461 0.7461
No log 2.0 248 0.9013 0.4938 0.5409 0.5023 0.6982 0.6982 0.6982 0.6982
No log 3.0 372 0.7797 0.5765 0.5451 0.5415 0.7635 0.7635 0.7635 0.7635
No log 4.0 496 0.7203 0.6530 0.5478 0.5409 0.7718 0.7718 0.7718 0.7718
0.9675 5.0 620 0.7465 0.5984 0.5960 0.5866 0.7777 0.7777 0.7777 0.7777
0.9675 6.0 744 0.7503 0.6134 0.5692 0.5699 0.7791 0.7791 0.7791 0.7791
0.9675 7.0 868 0.7665 0.6552 0.5732 0.5877 0.7864 0.7864 0.7864 0.7864
0.9675 8.0 992 0.7651 0.6253 0.5880 0.5937 0.7926 0.7926 0.7926 0.7926
0.5065 9.0 1116 0.8560 0.6075 0.5930 0.5945 0.7767 0.7767 0.7767 0.7767
0.5065 10.0 1240 0.8643 0.6354 0.5842 0.5972 0.7902 0.7902 0.7902 0.7902
0.5065 11.0 1364 0.9259 0.6337 0.5884 0.6021 0.7895 0.7895 0.7895 0.7895

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.0+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1