3v324v23's picture
add model
0c0a16a
metadata
license: mit
tags:
  - generated_from_keras_callback
model-index:
  - name: XLMRobertaTrainedOnSWEz
    results: []

XLMRobertaTrainedOnSWEz

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

  • Train Loss: 0.5177
  • Train End Logits Accuracy: 0.8335
  • Train Start Logits Accuracy: 0.8275
  • Validation Loss: 1.0855
  • Validation End Logits Accuracy: 0.7143
  • Validation Start Logits Accuracy: 0.7089
  • Epoch: 3

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:

  • optimizer: {'name': 'Adam', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 29248, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
  • training_precision: float32

Training results

Train Loss Train End Logits Accuracy Train Start Logits Accuracy Validation Loss Validation End Logits Accuracy Validation Start Logits Accuracy Epoch
1.3112 0.6049 0.5996 0.9920 0.6931 0.6899 0
0.8736 0.7267 0.7230 0.9677 0.7119 0.7100 1
0.6621 0.7879 0.7839 1.0244 0.7074 0.7058 2
0.5177 0.8335 0.8275 1.0855 0.7143 0.7089 3

Framework versions

  • Transformers 4.20.1
  • TensorFlow 2.6.4
  • Datasets 2.1.0
  • Tokenizers 0.12.1