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metadata
license: mit
tags:
  - generated_from_keras_callback
model-index:
  - name: xmelus/invoices-roberta-large
    results: []

xmelus/invoices-roberta-large

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

  • Train Loss: 2.2317
  • Train Accuracy: 0.0883
  • Validation Loss: 2.1699
  • Validation Accuracy: 0.0899
  • Finished epochs: 13

Training hyperparameters

The following hyperparameters were used during training:

  • optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 754, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'passive_serialization': True}, 'warmup_steps': 1000, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
  • training_precision: mixed_float16

Training results

Train Loss Train Accuracy Validation Loss Validation Accuracy Epoch
11.4516 0.0165 4.5115 0.0501 0
3.6182 0.0628 2.8398 0.0752 1
2.2317 0.0883 2.1699 0.0899 2
1.9700 0.0942 2.5529 0.0831 3
1.9714 0.0941 2.4961 0.0843 4
1.9682 0.0940 2.5089 0.0839 5
1.9546 0.0944 2.5029 0.0841 6
1.9808 0.0939 2.5140 0.0838 7
1.9728 0.0937 2.5212 0.0833 8
1.9655 0.0941 2.5575 0.0838 9
1.9708 0.0935 2.5419 0.0833 10
1.9693 0.0940 2.5304 0.0836 11
1.9614 0.0941 2.5176 0.0835 12

Framework versions

  • Transformers 4.21.2
  • TensorFlow 2.8.2
  • Datasets 2.4.0
  • Tokenizers 0.12.1