horger89/SlightlyFineTunedBertOnSquad

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

• Train Loss: 6.5399
• Train End Logits Loss: 3.1546
• Train Start Logits Loss: 3.3853
• Train End Logits Accuracy: 0.3726
• Train Start Logits Accuracy: 0.3301
• Validation Loss: 6.1757
• Validation End Logits Loss: 3.0226
• Validation Start Logits Loss: 3.1531
• Validation End Logits Accuracy: 0.4046
• Validation Start Logits Accuracy: 0.3661
• Epoch: 2

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': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 5250, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
• training_precision: float32

Training results

Train Loss	Train End Logits Loss	Train Start Logits Loss	Train End Logits Accuracy	Train Start Logits Accuracy	Validation Loss	Validation End Logits Loss	Validation Start Logits Loss	Validation End Logits Accuracy	Validation Start Logits Accuracy	Epoch
8.3613	4.1160	4.2453	0.1252	0.1231	7.2387	3.6778	3.5609	0.2866	0.2680	0
7.4922	3.5571	3.9351	0.2865	0.2273	6.9356	3.5662	3.3694	0.3823	0.3239	1
6.5399	3.1546	3.3853	0.3726	0.3301	6.1757	3.0226	3.1531	0.4046	0.3661	2

Framework versions

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