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llama3-section-classifier – AI Model by dklpp | AlphaNeural AI
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dklpp
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llama3-section-classifier
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peft
safetensors
adapter
lora
transformers
meta-llama/Llama-3.1-8B-Instruct
llama3.1
us
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llama3-section-classifier
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:
Loss: 1.1236
Accuracy: 0.6536
Precision: 0.6613
Recall: 0.6536
F1: 0.6553
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: 8
total_train_batch_size: 32
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
Precision
Recall
F1
9.6616
1.0
310
1.1046
0.6464
0.6476
0.6464
0.6244
7.0864
2.0
620
1.0653
0.64
0.6520
0.64
0.6414
4.771
3.0
930
1.1236
0.6536
0.6613
0.6536
0.6553
Framework versions
PEFT 0.17.1
Transformers 4.57.1
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1
