CIS6930_DAAGR_T5_NoEmo

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: 0.3368
• Train Accuracy: 0.9629
• Validation Loss: 0.4438
• Validation Accuracy: 0.9496
• Epoch: 17

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 Accuracy	Validation Loss	Validation Accuracy	Epoch
0.5062	0.9405	0.4590	0.9454	0
0.4381	0.9479	0.4477	0.9472	1
0.4249	0.9499	0.4423	0.9481	2
0.4152	0.9513	0.4386	0.9486	3
0.4071	0.9525	0.4365	0.9490	4
0.4000	0.9535	0.4349	0.9493	5
0.3935	0.9545	0.4338	0.9496	6
0.3876	0.9553	0.4337	0.9498	7
0.3816	0.9562	0.4338	0.9498	8
0.3763	0.9571	0.4343	0.9499	9
0.3708	0.9578	0.4338	0.9500	10
0.3657	0.9586	0.4357	0.9498	11
0.3605	0.9593	0.4355	0.9500	12
0.3556	0.9601	0.4370	0.9499	13
0.3507	0.9608	0.4380	0.9499	14
0.3463	0.9615	0.4397	0.9498	15
0.3413	0.9622	0.4427	0.9496	16
0.3368	0.9629	0.4438	0.9496	17

Framework versions

• Transformers 4.27.4
• TensorFlow 2.11.0
• Datasets 2.11.0
• Tokenizers 0.13.2