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mistral-medquad-r32 – AI Model by vlachner | AlphaNeural AI
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vlachner
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mistral-medquad-r32
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peft
safetensors
mistral
lora
qlora
medquad
fine-tuning
en
lavita/MedQuAD
mistralai/Mistral-7B-Instruct-v0.3
adapter
apache-2.0
us
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Mistral 7B MedQuAD (LoRA r=32)
Training configuration
Epochs: 1
Batch size: 1
Gradient accumulation: 4
Learning rate: 2e-4
Optimizer: paged_adamw_8bit
Quantization: 4-bit (bitsandbytes)
Training Summary
Step
Training Loss
Validation Loss
Mean Token Accuracy
20
1.1077
1.0624
0.7329
100
0.7190
0.8991
0.7721
200
0.9566
0.8750
0.7758
300
0.9045
0.8575
0.7783
400
1.0345
0.8418
0.7806
500
0.9336
0.8355
0.7817
Final metrics
Final Training Loss:
0.90
Final Validation Loss:
0.84
Final Mean Token Accuracy:
0.78
Epochs:
1
Total Steps:
500
Model fine-tuned on the MedQuAD dataset for medical QA using PEFT + QLoRA with rank = 32.
