albert-base-v2-CancerFarore-Model – AI Model by cancerfarore | AlphaNeural AI

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cancerfarore/
albert-base-v2-CancerFarore-Model

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cancerfarore/albert-base-v2-CancerFarore-Model

This model is a fine-tuned version of albert/albert-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:

Train Loss: 0.7456
Train End Logits Accuracy: 0.7778
Train Start Logits Accuracy: 0.7525
Validation Loss: 0.9444
Validation End Logits Accuracy: 0.7069
Validation Start Logits Accuracy: 0.6994
Epoch: 1

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': 3798, '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 Accuracy	Train Start Logits Accuracy	Validation Loss	Validation End Logits Accuracy	Validation Start Logits Accuracy	Epoch
1.2646	0.6255	0.6055	0.9592	0.6964	0.6829	0
0.7456	0.7778	0.7525	0.9444	0.7069	0.6994	1

Framework versions

Transformers 4.40.1
TensorFlow 2.15.0
Datasets 2.19.0
Tokenizers 0.19.1