Qwen3.6 27B Slo Med Mt LoRA v3

--- library_name: peft license: other license_name: qwen language: - sl - en base_model: llmfan46/Qwen3.6-27B-uncensored-heretic-v2-Native-MTP-Preserved tags: - base_model:adapter:llmfan46/Qwen3.6-27B-uncensored-heretic-v2-Native-MTP-Preserved - llama-factory - lora - transformers pipeline_tag: text-generation model-index: - name: qwen27b_dense_slo_medical_v3 results: [] --- # Qwen3.6-27B Slovenian medical — experimental LoRA v3 > Trained by **[MediaAtlas](https://mediaatlas.si/ai-training.html)** — LLM fine-tuning on your own data, trained in the EU, weights delivered. [Pricing](https://mediaatlas.si/ai-training-pricing.html) · [All our models](https://huggingface.co/texdata) **Na kratko:** Poskusni adapter LoRA (27B): kratek SFT na sintetičnem slovenskem medicinskem naboru (v3) z naborom za ohranjanje pogovora. Raziskovalni artefakt, ni evalviran, ni za klinično rabo. Za prevajanje uporabite `texdata/Qwen3.6-27B-slo-med-mt`. This model is a fine-tuned version of [llmfan46/Qwen3.6-27B-uncensored-heretic-v2-Native-MTP-Preserved](https://huggingface.co/llmfan46/Qwen3.6-27B-uncensored-heretic-v2-Native-MTP-Preserved) on the sft_synthetic_med_v3 and the sft_chat_ret datasets. It achieves the following results on the evaluation set: - Loss: 0.6921 ## Model description An **experimental** LoRA adapter from a short supervised fine-tuning run (27 optimizer steps over 3 epochs, effective batch 32) on the internal `sft_synthetic_med_v3` set (synthetic Slovenian medical examples) plus `sft_chat_ret` (Slovenian chat retention). Published for transparency and reproducibility of our training runs. ## Intended uses & limitations Research only. **Not evaluated beyond validation loss**, not a medical device, not for clinical use; outputs may be wrong. For production-quality models see the main cards linked above. ## Training and evaluation data Internal sets `sft_synthetic_med_v3` and `sft_chat_ret`; held-out validation split of the same data (loss 0.6921). No external benchmark was run. ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - distributed_type: multi-GPU - num_devices: 2 - gradient_accumulation_steps: 8 - total_train_batch_size: 32 - total_eval_batch_size: 4 - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with...

--- library_name: peft license: other base_model: llmfan46/Qwen3.6-27B-uncensored-heretic-v2-Native-MTP-Preserved tags: - base_model:adapter:llmfan46/Qwen3.6-27B-uncensored-heretic-v2-Native-MTP-Preserved - llama-factory - lora - transformers pipeline_tag: text-generation model-index: - name: qwen27b_dense_slo_medical_v3 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # qwen27b_dense_slo_medical_v3 This model is a fine-tuned version of [llmfan46/Qwen3.6-27B-uncensored-heretic-v2-Native-MTP-Preserved](https://huggingface.co/llmfan46/Qwen3.6-27B-uncensored-heretic-v2-Native-MTP-Preserved) on the sft_synthetic_med_v3 and the sft_chat_ret datasets. It achieves the following results on the evaluation set: - Loss: 0.6921 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - distributed_type: multi-GPU - num_devices: 2 - gradient_accumulation_steps: 8 - total_train_batch_size: 32 - total_eval_batch_size: 4 - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 0.05 - num_epochs: 3.0 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 0.6318 | 3.0 | 27 | 0.6921 | ### Framework versions - PEFT 0.18.1 - Transformers 5.6.0 - Pytorch 2.12.1+cu130 - Datasets 4.0.0 - Tokenizers 0.22.2

Source context: 4 downloads · 0 likes · Pipeline text-generation · Library peft · Repo texdata/Qwen3.6-27B-slo-med-mt-LoRA-v3