Hyperledger15ALBERT_Unbalance – AI Model by YakovElm | AlphaNeural AI

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YakovElm/
Hyperledger15ALBERT_Unbalance

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text-classification

generated_from_keras_callback

autotrain_compatible

endpoints_compatible

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Hyperledger15ALBERT_Unbalance

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

Train Loss: 0.2366
Train Accuracy: 0.9184
Validation Loss: 0.3586
Validation Accuracy: 0.8807
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': 0.001, 'clipnorm': 1.0, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': False, 'is_legacy_optimizer': False, 'learning_rate': 3e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
training_precision: float32

Training results

Train Loss	Train Accuracy	Validation Loss	Validation Accuracy	Epoch
0.3122	0.9035	0.3451	0.8807	0
0.2972	0.9035	0.3392	0.8807	1
0.2977	0.9035	0.3292	0.8807	2
0.2768	0.9035	0.3324	0.8807	3
0.2529	0.9076	0.3699	0.8413	4
0.2366	0.9184	0.3586	0.8807	5

Framework versions

Transformers 4.29.2
TensorFlow 2.12.0
Datasets 2.12.0
Tokenizers 0.13.3