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Llama-3.1-8-QLoRA – AI Model by Pragades | AlphaNeural AI
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Pragades
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Llama-3.1-8-QLoRA
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peft
safetensors
trl
sft
generated_from_trainer
meta-llama/Llama-3.1-8B
adapter
llama3.1
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Llama-3.1-8-QLoRA
This model is a fine-tuned version of
meta-llama/Meta-Llama-3.1-8B
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.6936
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: 0.0001
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 1
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
1.2245
0.6329
100
0.6936
Framework versions
PEFT 0.12.0
Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.0.0
Tokenizers 0.19.1
