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qlora-llama70-ft-full-dataset – AI Model by aprilzoo | AlphaNeural AI
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qlora-llama70-ft-full-dataset
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meta-llama/Llama-2-70b-hf
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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
load_in_8bit: False
load_in_4bit: True
llm_int8_threshold: 6.0
llm_int8_skip_modules: None
llm_int8_enable_fp32_cpu_offload: False
llm_int8_has_fp16_weight: False
bnb_4bit_quant_type: nf4
bnb_4bit_use_double_quant: True
bnb_4bit_compute_dtype: float16
Training hyperparameters
The following hyperparameters were used during training:
learning_rate: 0.0025
train_batch_size: 2
eval_batch_size: 1
seed: 42
distributed_type: multi-GPU
num_devices: 8
total_train_batch_size: 16
total_eval_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 1
mixed_precision_training: 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
