t5-large-qdmr-grounded-with-db

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

• Loss: 0.1100

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: 5e-05
• train_batch_size: 1
• eval_batch_size: 4
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 2
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• training_steps: 20000

Training results

Training Loss	Epoch	Step	Validation Loss
0.2122	0.2312	500	0.1902
0.1786	0.4624	1000	0.1430
0.146	0.6936	1500	0.1148
0.1223	0.9249	2000	0.1092
0.0976	1.1561	2500	0.1100

Framework versions

• Transformers 4.40.2
• Pytorch 2.2.1+cu121
• Datasets 2.19.1
• Tokenizers 0.19.1