final_classifications

This model is a fine-tuned version of yhavinga/t5-small-24L-ccmatrix-multi on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.1005
• F1: {'f1': 0.9592760180995475}
• Precision: {'precision': 0.954954954954955}
• Recall: {'recall': 0.9636363636363636}

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: 0.0001
• 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: 6

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Precision	Recall
No log	1.0	110	0.2362	{'f1': 0.0}	{'precision': 0.0}	{'recall': 0.0}
No log	2.0	220	0.1164	{'f1': 0.9502262443438914}	{'precision': 0.9459459459459459}	{'recall': 0.9545454545454546}
No log	3.0	330	0.0832	{'f1': 0.9596412556053813}	{'precision': 0.9469026548672567}	{'recall': 0.9727272727272728}
No log	4.0	440	0.0918	{'f1': 0.9549549549549549}	{'precision': 0.9464285714285714}	{'recall': 0.9636363636363636}
0.1554	5.0	550	0.0939	{'f1': 0.9596412556053813}	{'precision': 0.9469026548672567}	{'recall': 0.9727272727272728}
0.1554	6.0	660	0.1005	{'f1': 0.9592760180995475}	{'precision': 0.954954954954955}	{'recall': 0.9636363636363636}

Framework versions

• Transformers 4.40.1
• Pytorch 2.2.1+cu121
• Datasets 2.19.0
• Tokenizers 0.19.1