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Model: kth8/gemma-3-270m-it-Email-Generator
Source: Original Platform

README.md

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+---
+license: gemma
+language:
+- en
+base_model: unsloth/gemma-3-270m-it
+datasets:
+- Kamisori-daijin/email-datasets-20k
+pipeline_tag: text-generation
+library_name: transformers
+tags:
+- sft
+- trl
+- unsloth
+- google
+- gemma
+- gemma3
+- gemma3_text
+---
+![logo](https://storage.googleapis.com/gweb-developer-goog-blog-assets/images/gemma-3_2.original.png)
+A fine-tune of [unsloth/gemma-3-270m-it](https://huggingface.co/unsloth/gemma-3-270m-it) on the [Kamisori-daijin/email-datasets-20k](https://huggingface.co/datasets/Kamisori-daijin/email-datasets-20k) dataset.
+
+## Usage example
+**System prompt**
+```
+You are a helpful assistant.
+```
+**User prompt**
+```
+Write a direct and concise business email(under 200 words) from a Founder to a Angry Shareholder regarding notifying about a price change, specifically after winning a major award.
+```
+**Assistant response**
+```
+Subject: Regarding Pricing Update - [Company Name]
+
+Dear [Shareholder Name],
+
+I'm writing to address your concerns regarding our recent pricing update. You’re right to raise questions, and I want to be transparent about the reasoning behind it.
+
+We’re incredibly proud to announce that [Company Name] recently won the [Award Name] award – a significant validation of our innovative product and market position. This achievement, coupled with increased customer demand, has necessitated a modest price adjustment to ensure we can continue investing in product development and deliver the exceptional service our customers expect.
+
+We remain confident in the value we provide and believe this change will ultimately benefit all our stakeholders. We welcome the opportunity to discuss this further with you.
+
+Sincerely,
+[Name]
+Founder, [Company Name]
+```
+## Model Details
+- Base Model: `unsloth/gemma-3-270m-it`
+- Parameter Count: 268,098,176
+- Precision: torch.bfloat16
+
+## Hardware
+- GPU: NVIDIA RTX PRO 6000 Blackwell Server Edition
+- Announced: Mar 17th, 2025
+- Release Date: Mar 18th, 2025
+- Memory Type: GDDR7
+- Bandwidth: 1.79 TB/s
+- Memory Size: 96 GB
+- Memory Bus: 512 bit
+- Shading Units: 24064
+- TDP: 600W
+
+## Training Settings
+### PEFT
+- Rank: 32
+- LoRA alpha: 64
+- Modules: q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj
+- Gradient checkpointing: unsloth
+
+### SFT
+- Epoch: 4
+- Batch size: 32
+- Gradient Accumulation steps: 1
+- Warmup ratio: 0.05
+- Learning rate: 0.0002
+- Optimizer: adamw_torch_fused
+- Learning rate scheduler: cosine
+
+## Training stats
+- Date: 2026-03-25T12:51:43.831886
+- Peak VRAM usage: 16.834 GB
+- Global step: 2360
+- Training runtime (seconds): 470.094
+- Average training loss: 1.2040837437419567
+- Final validation loss: 1.2054944038391113
+
+## Framework versions
+- Unsloth: 2026.3.11
+- TRL: 0.22.2
+- Transformers: 4.56.2
+- Pytorch: 2.10.0+cu128
+- Datasets: 4.8.4
+- Tokenizers: 0.22.2
+
+## License
+This model is released under the Gemma license. See the [Gemma Terms of Use](https://ai.google.dev/gemma/terms) and [Prohibited Use Policy](https://policies.google.com/terms/generative-ai/use-policy) regarding the use of Gemma-generated content.