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llama3_qlora_results – AI Model by amirbhat | AlphaNeural AI
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llama3_qlora_results
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peft
safetensors
adapter
lora
transformers
meta-llama/Llama-3.1-8B-Instruct
llama3.1
us
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llama3_qlora_results
This model is a fine-tuned version of
meta-llama/Llama-3.1-8B-Instruct
on the None dataset. It achieves the following results on the evaluation set:
eval_loss: 0.8613
eval_model_preparation_time: 0.0001
eval_accuracy: 0.6764
eval_f1: 0.6798
eval_runtime: 1609.0006
eval_samples_per_second: 5.411
eval_steps_per_second: 1.353
step: 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
gradient_accumulation_steps: 4
total_train_batch_size: 16
optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
training_steps: 200
Framework versions
PEFT 0.18.1
Transformers 5.0.0
Pytorch 2.10.0+cu128
Datasets 4.8.3
Tokenizers 0.22.2
