my_t5 – AI Model by Thangnv | AlphaNeural AI

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Thangnv/
my_t5

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text2text-generation

generated_from_keras_callback

google-t5/t5-small

endpoints_compatible

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Thangnv/my_t5

This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:

Train Loss: 0.4858
Train Sparse Categorical Accuracy: 0.8583
Validation Loss: 0.4856
Validation Sparse Categorical Accuracy: 0.8604
Epoch: 9

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': 0.001, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
training_precision: float32

Training results

Train Loss	Train Sparse Categorical Accuracy	Validation Loss	Validation Sparse Categorical Accuracy	Epoch
0.7764	0.7851	0.6316	0.8233	0
0.6144	0.8267	0.5740	0.8381	1
0.5726	0.8371	0.5442	0.8455	2
0.5483	0.8431	0.5273	0.8501	3
0.5315	0.8472	0.5156	0.8527	4
0.5187	0.8503	0.5060	0.8554	5
0.5083	0.8529	0.4995	0.8572	6
0.4997	0.8549	0.4955	0.8581	7
0.4923	0.8567	0.4895	0.8596	8
0.4858	0.8583	0.4856	0.8604	9

Framework versions

Transformers 4.33.2
TensorFlow 2.13.0
Datasets 2.14.5
Tokenizers 0.13.3