t5-small-ret-conceptnet2

This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.1709
• Acc: {'accuracy': 0.8700980392156863}
• Precision: {'precision': 0.811340206185567}
• Recall: {'recall': 0.9644607843137255}
• F1: {'f1': 0.8812989921612542}

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:

• learning_rate: 2e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 1
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Acc	Precision	Recall	F1
0.1989	1.0	721	0.1709	{'accuracy': 0.8700980392156863}	{'precision': 0.811340206185567}	{'recall': 0.9644607843137255}	{'f1': 0.8812989921612542}

Framework versions

• Transformers 4.25.1
• Pytorch 1.13.0+cu116
• Datasets 2.7.1
• Tokenizers 0.13.2