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Llama2-7b-BoolQ-full-LoRA – AI Model by mogmyij | AlphaNeural AI
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Llama2-7b-BoolQ-full-LoRA
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peft
safetensors
trl
sft
generated_from_trainer
meta-llama/Llama-2-7b-hf
adapter
llama2
us
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Llama2-7b-BoolQ-full-LoRA
This model is a fine-tuned version of
meta-llama/Llama-2-7b-hf
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.5874
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: 2
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.05
num_epochs: 3
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
0.5743
0.9996
1178
0.3069
0.3457
2.0
2357
0.3704
0.9745
2.9987
3534
0.5874
Framework versions
PEFT 0.11.1
Transformers 4.41.1
Pytorch 2.3.0
Datasets 2.19.1
Tokenizers 0.19.1
