cruiser/twitter_roberta_final_model

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

• Train Loss: 0.0648
• Validation Loss: 1.0107
• Train Accuracy: 0.7943
• Epoch: 9

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', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 1e-05, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 1e-05, 'decay_steps': 34090, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'passive_serialization': True}, 'warmup_steps': 250, 'power': 1.0, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
• training_precision: float32

Training results

Train Loss	Validation Loss	Train Accuracy	Epoch
0.5482	0.4911	0.7991	0
0.4389	0.5053	0.7972	1
0.3567	0.5357	0.7935	2
0.2774	0.6193	0.7872	3
0.2080	0.6732	0.7989	4
0.1545	0.7639	0.7889	5
0.1162	0.8836	0.7855	6
0.0943	0.9301	0.7903	7
0.0768	0.9647	0.7929	8
0.0648	1.0107	0.7943	9

Framework versions

• Transformers 4.27.4
• TensorFlow 2.11.0
• Datasets 2.1.0
• Tokenizers 0.13.2