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Gemma E2B Fine-Tuned Model
This repository contains a fine-tuned version of google/gemma-4-E2B-it trained using LoRA-based supervised fine-tuning (SFT).
Base Model
- Base model: google/gemma-4-E2B-it
- Architecture: Gemma 4
- Model type: Causal Language Model
- License: Gemma License
Fine-Tuning Method
This model was fine-tuned using:
- LoRA (Low-Rank Adaptation)
- BF16 mixed precision training
- Hugging Face Transformers
- TRL SFTTrainer
- PEFT
- PyTorch
The final uploaded checkpoint is a fully merged model export, meaning the LoRA weights have already been merged into the base model weights.
Training Setup
Training environment:
- GPU: NVIDIA A100
- CUDA: 12.x
- Precision: BF16
- Optimizer: adamw_torch_fused
LoRA Configuration
- Rank (r): 16
- Alpha: 16
- Dropout: 0.05
Dataset
The model was trained on ABS regulatory QAs.
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