provenance-synthetic-small

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

• Loss: 0.0006
• Accuracy: 0.9997

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: 4
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 64
• optimizer: Use adafactor and the args are: No additional optimizer arguments
• lr_scheduler_type: linear
• training_steps: 10000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.023	0.64	1000	0.0019	0.9999
0.006	1.2797	2000	0.0012	0.9999
0.0038	1.9197	3000	0.0010	0.9999
0.0028	2.5594	4000	0.0009	0.9999
0.0024	3.1990	5000	0.0008	0.9996
0.0021	3.8390	6000	0.0007	0.9997
0.0021	4.4787	7000	0.0007	0.9997
0.0018	5.1184	8000	0.0007	0.9997
0.0018	5.7584	9000	0.0006	0.9997
0.0018	6.3981	10000	0.0006	0.9997

Framework versions

• Transformers 4.52.3
• Pytorch 2.7.0+cu126
• Datasets 3.6.0
• Tokenizers 0.21.1