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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
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