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metadata
library_name: transformers
license: mit
base_model: roberta-base
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: roberta-base_LOGIC_LRTC
    results: []

roberta-base_LOGIC_LRTC

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

  • Loss: 1.9419
  • Accuracy: 0.6933
  • Macro Precision: 0.6604
  • Macro F1: 0.6503

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: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • num_epochs: 12

Training results

Training Loss Epoch Step Validation Loss Accuracy Macro Precision Macro F1
No log 1.0 116 1.5639 0.41 0.4728 0.3904
No log 2.0 232 1.1501 0.5833 0.5591 0.5659
No log 3.0 348 1.1315 0.64 0.6182 0.6220
No log 4.0 464 1.2345 0.67 0.6471 0.6237
0.9897 5.0 580 1.3952 0.62 0.5912 0.5960
0.9897 6.0 696 1.5032 0.68 0.6370 0.6407
0.9897 7.0 812 1.6859 0.6833 0.6437 0.6478
0.9897 8.0 928 1.9130 0.69 0.6638 0.6393
0.0959 9.0 1044 1.9246 0.68 0.6526 0.6459
0.0959 10.0 1160 1.8800 0.6867 0.6378 0.6392
0.0959 11.0 1276 1.9436 0.69 0.6623 0.6519
0.0959 12.0 1392 1.9419 0.6933 0.6604 0.6503

Framework versions

  • Transformers 5.0.0
  • Pytorch 2.10.0+cu128
  • Datasets 4.0.0
  • Tokenizers 0.22.2