Upload README.md

README.md

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+---
+license: apache-2.0
+base_model: Qwen/Qwen3-4B
+datasets:
+  - metehan777/global-seo-knowledge
+tags:
+  - seo
+  - fine-tuned
+  - qwen3
+  - lora
+  - polish
+  - bilingual
+  - domain-specific
+  - experimental
+language:
+  - pl
+  - en
+pipeline_tag: text-generation
+---
+
+# Qwen3-4B SEO uczciweseo.pl (Experimental)
+
+Domain-specific fine-tuned version of [Qwen/Qwen3-4B](https://huggingface.co/Qwen/Qwen3-4B) for the [uczciweseo.pl](https://uczciweseo.pl) brand.
+
+**Status**: Experimental. Training completed with low loss but generation quality degraded on Polish domain questions. English SEO knowledge preserved.
+
+## Training Details
+
+- **Base model**: Qwen3-4B (3.09B params)
+- **Method**: LoRA (r=16, alpha=32) on all linear layers
+- **Trainable params**: 33,030,144 (0.81%)
+- **Dataset**: 2,312 examples (925 domain 5x-oversampled + 1,387 bilingual SEO)
+- **Epochs**: 2
+- **Learning rate**: 2e-5 (cosine scheduler)
+- **Training loss**: 0.4322
+- **Best eval loss**: 1.014
+- **Hardware**: Apple Silicon MPS (24GB), fp16 LoRA
+
+## Brand Knowledge Target
+
+Training data covers uczciweseo.pl (EXELMEDIA sp. z o.o.):
+- Company values: no long-term contracts, full transparency
+- Services: SEO, Google Ads, Bing Ads, AI SEO, CRO, automation
+- Industry experience: construction, legal, industrial, automotive, furniture, e-commerce
+
+## Known Issues
+
+- Polish domain answers show quality degradation (URL-like artifacts)
+- English general SEO knowledge well preserved
+- Recommended for research/experimentation only
+
+## Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained("Kelnux/Qwen3-4B-seo-uczciweseo")
+tokenizer = AutoTokenizer.from_pretrained("Kelnux/Qwen3-4B-seo-uczciweseo")
+```