aprilzoo/qlora-llama70-ft-full-dataset

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qlora-llama70-ft-full-dataset

This model is a fine-tuned version of meta-llama/Llama-2-70b-hf on an unknown dataset. It achieves the following results on the evaluation set:

• —Loss: 1.5429

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

The following bitsandbytes quantization config was used during training:

• —quant_method: bitsandbytes
• —loadin8bit: False
• —loadin4bit: True
• —llmint8threshold: 6.0
• —llmint8skip_modules: None
• —llmint8enablefp32cpu_offload: False
• —llmint8hasfp16weight: False
• —bnb4bitquant_type: nf4
• —bnb4bitusedoublequant: True
• —bnb4bitcompute_dtype: float16

Training hyperparameters

The following hyperparameters were used during training:

• —learning_rate: 0.0025
• —trainbatchsize: 2
• —evalbatchsize: 1
• —seed: 42
• —distributed_type: multi-GPU
• —num_devices: 8
• —totaltrainbatch_size: 16
• —totalevalbatch_size: 8
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —num_epochs: 1
• —mixedprecisiontraining: Native AMP

Training results

Framework versions

• —PEFT 0.5.0
• —Transformers 4.36.2
• —Pytorch 2.1.2+cu121
• —Datasets 2.14.1
• —Tokenizers 0.15.0