gustavokpc/en_MODEL_bert-base-uncased_LRATE_1e-05_EPOCHS_7

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

• Train Loss: 0.0150
• Train Accuracy: 0.9951
• Train F1 M: 0.5657
• Train Precision M: 0.4067
• Train Recall M: 0.9873
• Validation Loss: 0.1309
• Validation Accuracy: 0.9655
• Validation F1 M: 0.5737
• Validation Precision M: 0.4163
• Validation Recall M: 0.9980
• 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': 1e-05, 'decay_steps': 3962, '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 Accuracy	Train F1 M	Train Precision M	Train Recall M	Validation Loss	Validation Accuracy	Validation F1 M	Validation Precision M	Validation Recall M	Epoch
0.1966	0.9215	0.4030	0.3067	0.6414	0.0842	0.9708	0.5427	0.4013	0.9115	0
0.0631	0.9799	0.5517	0.4014	0.9425	0.0667	0.9726	0.5583	0.4067	0.9621	1
0.0305	0.9912	0.5630	0.4059	0.9778	0.0696	0.9779	0.5517	0.4013	0.9580	2
0.0150	0.9951	0.5657	0.4067	0.9873	0.1309	0.9655	0.5737	0.4163	0.9980	3

Framework versions

• Transformers 4.34.1
• TensorFlow 2.10.0
• Datasets 2.14.5
• Tokenizers 0.14.1