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lora-llama3.2-3B-mcq – AI Model by tommypraa | AlphaNeural AI
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lora-llama3.2-3B-mcq
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peft
tensorboard
safetensors
generated_from_trainer
meta-llama/Llama-3.2-3B
adapter
llama3.2
us
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lora-llama3.2-3B-mcq
This model is a fine-tuned version of
meta-llama/Llama-3.2-3B
on the None dataset. It achieves the following results on the evaluation set:
Loss: 2.0528
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: 2
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 16
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
No log
0.8276
3
2.1547
No log
1.8276
6
2.0878
No log
2.8276
9
2.0528
Framework versions
PEFT 0.14.0
Transformers 4.50.0
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1
