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Q32_continent – AI Model by shirleyah | AlphaNeural AI
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shirleyah
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Q32_continent
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peft
tensorboard
safetensors
trl
sft
generated_from_trainer
meta-llama/Meta-Llama-3-8B-Instruct
adapter
llama3
us
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Q32_continent
This model is a fine-tuned version of
meta-llama/Meta-Llama-3-8B-Instruct
on an unknown dataset.
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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant
lr_scheduler_warmup_ratio: 0.03
num_epochs: 3
Training results
Framework versions
PEFT 0.11.2.dev0
Transformers 4.41.1
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1
