Model
| Metric | Value |
|---|---|
| Model | Svngoku/qwen3-black-mirror (https://huggingface.co/Svngoku/qwen3-black-mirror) |
| Base | Qwen3-0.6B-Base (4-bit) |
| Data | 33 episodes across 7 seasons, auto-merged |
| Epochs | 3 |
| Steps | 15 |
| Training time | 25 seconds |
| Loss | 3.08 -> 2.09 (epoch 2) -> 2.54 (epoch 3) |
| Upload | Merged 16-bit model (1.19 GB) |
| The model was merged (LoRA weights folded into the base model) and pushed as a standalone model to Svngoku/qwen3-black-mirror. The inference test shows it's generating coherent text with some thematic influence (surveillance, privacy, ratings -- very Black Mirror). | |
| Artifacts created: |
- scripts/continued-pretraining.py -- custom script with multi-split support
- Svngoku/black-mirror-training (https://huggingface.co/datasets/Svngoku/black-mirror-training) -- HF dataset repo hosting the script
- Svngoku/qwen3-black-mirror (https://huggingface.co/Svngoku/qwen3-black-mirror) -- the trained model
- Svngoku/qwen3-black-mirror-test (https://huggingface.co/Svngoku/qwen3-black-mirror-test) -- dry-run LoRA adapter
Uploaded finetuned model
- Developed by: Svngoku
- License: apache-2.0
- Finetuned from model : unsloth/Qwen3-0.6B-Base-unsloth-bnb-4bit
This qwen3 model was trained 2x faster with Unsloth and Huggingface's TRL library.
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