tilyupo/t5-small-trivia-ca2q

t5-small-trivia-v2-ca2q

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

• Train Loss: 0.3095
• Validation Loss: 0.3903
• Epoch: 3

{'eval_loss': 1.3911314010620117,
 'eval_bleu': 17.919726187841192,
 'eval_rouge1': 54.15,
 'eval_rouge2': 31.12,
 'eval_rougeL': 47.29,
 'eval_rougeLsum': 47.32,
 'eval_exact': 0.020600524730346906,
 'eval_runtime': 104.3595,
 'eval_samples_per_second': 98.611,
 'eval_steps_per_second': 3.085}

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': 'Adafactor', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': False, 'is_legacy_optimizer': False, 'learning_rate': 0.001, 'beta_2_decay': -0.8, 'epsilon_1': 1e-30, 'epsilon_2': 0.001, 'clip_threshold': 1.0, 'relative_step': False}
• training_precision: float32

Training results

Train Loss	Validation Loss	Epoch
0.6099	0.4054	0
0.3919	0.3899	1
0.3451	0.3880	2
0.3095	0.3903	3

Framework versions

• Transformers 4.31.0
• TensorFlow 2.12.0
• Datasets 2.14.3
• Tokenizers 0.13.3