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AnomalyCoT_llama3.2_vision_sft_checkpoint – AI Model by Marine0506 | AlphaNeural AI
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Marine0506
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AnomalyCoT_llama3.2_vision_sft_checkpoint
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peft
safetensors
llama-factory
lora
generated_from_trainer
meta-llama/Llama-3.2-11B-Vision-Instruct
adapter
other
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Llama-3.2-11B-Vision-Instruct_lora_cot
This model is a fine-tuned version of [meta-llama/Llama-3.2-11B-Vision-Instruct(
https://huggingface.co/meta-llama/Llama-3.2-11B-Vision-Instruct
) on the industrial_qa_cot dataset. It achieves the following results on the evaluation set:
Loss: 0.4842
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: 4
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 32
optimizer: Use adamw_torch 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: 3.0
Training results
Training Loss
Epoch
Step
Validation Loss
0.5922
0.5996
500
0.5888
0.5281
1.1991
1000
0.5327
0.5061
1.7987
1500
0.5039
0.4397
2.3981
2000
0.4895
0.4517
2.9978
2500
0.4842
Framework versions
PEFT 0.15.2
Transformers 4.52.4
Pytorch 2.7.1+cu126
Datasets 3.6.0
Tokenizers 0.21.1
