dax_query_llama

This model is a fine-tuned version of meta-llama/Llama-3.1-8B on the None dataset. It achieves the following results on the evaluation set:

• Loss: 9.5530
• Rouge1: 0.3920
• Rouge2: 0.0986
• Rougel: 0.3668
• Rougelsum: 0.3670

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: 0.0002
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 16
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.03
• num_epochs: 3
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
No log	1.0	1	9.5530	0.3920	0.0986	0.3668	0.3670
No log	2.0	2	9.5530	0.3920	0.0986	0.3668	0.3670
No log	3.0	3	9.5530	0.3920	0.0986	0.3668	0.3670

Framework versions

• PEFT 0.14.0
• Transformers 4.47.1
• Pytorch 2.5.1+cu118
• Datasets 3.2.0
• Tokenizers 0.21.0