Thangnv/t5

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

• Train Loss: 0.6838
• Train Sparse Categorical Accuracy: 0.8193
• Validation Loss: 0.6798
• Validation Sparse Categorical Accuracy: 0.8227
• 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', '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
0.8162	0.7924	0.7433	0.8094	0
0.7413	0.8077	0.7142	0.8151	1
0.7069	0.8147	0.6927	0.8199	2
0.6838	0.8193	0.6798	0.8227	3

Framework versions

• Transformers 4.33.2
• TensorFlow 2.13.0
• Datasets 2.14.5
• Tokenizers 0.13.3