XLMRobertaz

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: 0.5404
• Train End Logits Accuracy: 0.8404
• Train Start Logits Accuracy: 0.7997
• Validation Loss: 1.0036
• Validation End Logits Accuracy: 0.7448
• Validation Start Logits Accuracy: 0.7148
• 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': 22396, '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
1.2940	0.6600	0.6215	0.9820	0.7357	0.7047	0
0.8412	0.7666	0.7252	0.9281	0.7473	0.7137	1
0.6629	0.8091	0.7681	0.9387	0.7450	0.7130	2
0.5404	0.8404	0.7997	1.0036	0.7448	0.7148	3

Framework versions

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