zephyr-7b-sft-qlora

This model is a fine-tuned version of LLM-PBE/Llama3.1-8b-instruct-LLMPC-Red-Team on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.2536

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: 4
• eval_batch_size: 8
• seed: 42
• distributed_type: multi-GPU
• num_devices: 4
• gradient_accumulation_steps: 2
• total_train_batch_size: 32
• total_eval_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 5.0

Training results

Training Loss	Epoch	Step	Validation Loss
0.3835	1.0	41	0.3792
0.3431	2.0	82	0.3488
0.2489	3.0	123	0.2568
0.2468	4.0	164	0.2538
0.2454	5.0	205	0.2536

Framework versions

• PEFT 0.10.0
• Transformers 4.45.2
• Pytorch 2.4.0+cu121
• Datasets 3.0.0
• Tokenizers 0.20.0