lulygavri/sub1-trans

This model is a fine-tuned version of dccuchile/bert-base-spanish-wwm-uncased on an unknown dataset. It achieves the following results on the evaluation set:

• Train Loss: 0.0428
• Validation Loss: 0.4923
• Train Accuracy: 0.9
• Train Precision: [0.90909091 0. ]
• Train Precision W: 0.8273
• Train Recall: [0.98901099 0. ]
• Train Recall W: 0.9
• Train F1: [0.94736842 0. ]
• Train F1 W: 0.8621
• Epoch: 5

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': {'module': 'transformers.optimization_tf', 'class_name': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 34, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'warmup_steps': 500, 'power': 1.0, 'name': None}, 'registered_name': 'WarmUp'}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
• training_precision: float32

Training results

Train Loss	Validation Loss	Train Accuracy	Train Precision	Train Precision W	Train Recall	Train Recall W	Train F1	Train F1 W	Epoch
0.6479	0.4942	0.91	[0.91 0. ]	0.8281	[1. 0.]	0.91	[0.95287958 0. ]	0.8671	1
0.4492	0.4305	0.8	[0.9382716 0.21052632]	0.8728	[0.83516484 0.44444444]	0.8	[0.88372093 0.28571429]	0.8299	2
0.1358	0.3080	0.88	[0.90721649 0. ]	0.8256	[0.96703297 0. ]	0.88	[0.93617021 0. ]	0.8519	3
0.0545	0.3801	0.9	[0.90909091 0. ]	0.8273	[0.98901099 0. ]	0.9	[0.94736842 0. ]	0.8621	4
0.0428	0.4923	0.9	[0.90909091 0. ]	0.8273	[0.98901099 0. ]	0.9	[0.94736842 0. ]	0.8621	5

Framework versions

• Transformers 4.38.2
• TensorFlow 2.15.0
• Datasets 2.18.0
• Tokenizers 0.15.2