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gemma-4-E4B-20260610190427-v2
peerbench/gemma-4-E4B-20260610190427-v2
gemma-4-E4B-20260610190427-v2 is a image-text-to-text model from peerbench. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as gemma.
Fine-tuned unsloth/gemma-4-E4B-it on a curated, native-heavy German SFT corpus to improve general German skill (not a single benchmark). SFT · LoRA · bf16 · reasoning OFF.
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At a glance
- Task
- Image-Text-to-Text
- Library
- transformers
- License
- gemma
- Model type
- gemma4
- Access
- Public
- Created
- Jun 10, 2026
- Updated
- Jun 10, 2026
- SHA
- a22ce6c8
Try a prompt
Base models
Model card
From the Hugging Face model README
gemma-4-E4B — German SFT — gemma4-de-v2 (20260610190427 UTC)
Fine-tuned unsloth/gemma-4-E4B-it on a curated, native-heavy German SFT corpus to improve general German skill (not a single benchmark). SFT · LoRA · bf16 · reasoning OFF.
Variant: v2
Compute
- machine: 1x NVIDIA H100 80GB (a3-highgpu-1g, GCP us-central1-b)
- training wall-time: 101.5 min (1.0 epoch(s))
- final train_loss: 1.7187
Training parameters
- base: unsloth/gemma-4-E4B-it · quant bf16 (load_in_4bit=False, no QLoRA)
- lora_r 128 · alpha 256 · dropout 0.0 · target language+attn+mlp (vision frozen)
- lr 5e-05 · adamw_8bit · linear · warmup_steps 100
- per_device_batch 16 · grad_accum 1 · eff_batch 16 · max_seq 2048 · seed 3407
- chat_template gemma-4 (non-thinking) · train_on_responses_only
Data
- corpus: peerbench/gemma4-german-sft-corpus (split
gemma4-de-v2) — 25756 rows - native-heavy German + high-quality MT + balanced m_arc MCQ; per-source 20% cap; lang-ID + dedup; slimorca / ultra_chat excluded (noise / verbosity).
Logging
- W&B
gaa-mdk(entity forest-wb), rungemma-4-E4B-v2__sftmix-r128__20260610190427· date_utc 20260610190427
- Task
- Image-Text-to-Text
- Library
- transformers
- Type
- gemma4
- License
- gemma
- Created
- Jun 10, 2026
- Updated
- Jun 10, 2026