llama2-7b-qlora-finetuned

This model is a fine-tuned version of meta-llama/Llama-2-7b-hf on the None dataset. It achieves the following results on the evaluation set:

• Loss: 16.9329
• Accuracy: 0.0
• Rouge1: 0.0
• Rouge2: 0.0
• Rougel: 0.0

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
• distributed_type: multi-GPU
• num_devices: 2
• gradient_accumulation_steps: 16
• total_train_batch_size: 128
• total_eval_batch_size: 8
• 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_steps: 100
• num_epochs: 3
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Rouge1	Rouge2	Rougel
20.8734	1.4159	10	18.4987	0.0	0.0	0.0	0.0
20.0557	2.8319	20	16.9290	0.0	0.0	0.0	0.0

Framework versions

• PEFT 0.13.2
• Transformers 4.46.3
• Pytorch 2.4.1+cu121
• Datasets 3.0.1
• Tokenizers 0.20.0