CIS6930_DAAGR_T5_Emo

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: 0.3253
• Train Accuracy: 0.9647
• Validation Loss: 0.4468
• Validation Accuracy: 0.9495
• Epoch: 19

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
0.4976	0.9412	0.4567	0.9459	0
0.4359	0.9482	0.4462	0.9474	1
0.4228	0.9502	0.4406	0.9484	2
0.4131	0.9517	0.4370	0.9488	3
0.4050	0.9528	0.4349	0.9493	4
0.3981	0.9539	0.4335	0.9496	5
0.3914	0.9548	0.4327	0.9498	6
0.3851	0.9558	0.4328	0.9500	7
0.3794	0.9565	0.4328	0.9501	8
0.3738	0.9574	0.4321	0.9502	9
0.3685	0.9582	0.4328	0.9502	10
0.3632	0.9589	0.4340	0.9502	11
0.3582	0.9597	0.4343	0.9501	12
0.3531	0.9605	0.4363	0.9501	13
0.3482	0.9612	0.4381	0.9501	14
0.3436	0.9619	0.4390	0.9500	15
0.3391	0.9626	0.4396	0.9500	16
0.3340	0.9633	0.4438	0.9499	17
0.3297	0.9640	0.4454	0.9498	18
0.3253	0.9647	0.4468	0.9495	19

Framework versions

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