Model Card for Kurtis-EON1-Hybrid-2B-v0.1.2
[!WARNING] This repository contains experimental models designed strictly for academic evaluation and research purposes.
Critical Constraints:
- No Production Deployment: Experimental models must not be deployed in commercial, enterprise, or mission-critical environments under any circumstances.
- No Liability: Experimental models are provided "as-is" without warranties of any kind. The developers assume zero liability for downstream consequences, system integration failures, or regulatory non-compliance resulting from unauthorized deployment.
Model Details
Kurtis-EON1 is not a standard, overly-apologetic assistant.
Fine-tuned on highly curated empathetic and atmospheric datasets, this model is designed for deep, gothic contemplation, strict persona adherence and zero-drift multi-turn reasoning.
Model Description
- Developed by: ethicalabs.ai
- Model type: Echo-DSRN-Hybrid
- Language(s) (NLP): [More Information Needed]
- License: Apache 2.0
🏗️ Hybrid Architecture Details
| Property | Value |
|---|---|
| Base Model | Qwen2 |
| Total Parameters | 2.00B |
| Hidden Dim | 1536 |
| Attention Layers | 28 |
| DSRN Injectors | 9 |
| Injection Stride | 3 |
📊 Parameter Breakdown
| Component | Parameters | % of Total |
|---|---|---|
| Total | 2.00B | 100% |
| Embeddings | 233.37M | 11.67% |
| Backbone (Attention/MLP) | 1.31B | 65.51% |
| DSRN Injectors | 223.10M | 11.15% |
| LM Head | 233.37M | 11.67% |
🧩 DSRN Component (Per Injector)
| Sub-Component | Parameters | Description |
|---|---|---|
| Memory Gates | 8.26M | Recurrent state updates |
| Surprise Mechanism | 2.36M | Dynamic focus/gating |
🚀 Efficiency Metric
- DSRN Parameter Overhead: 12.55% additional parameters compared to base.
- Hybrid Ratio: 1 DSRN block for every 3 attention layers.
Model Sources
- Repository: Echo-DSRN
Evaluation
| Tasks | Version | Filter | n-shot | Metric | Value | Stderr | ||
|---|---|---|---|---|---|---|---|---|
| arc_challenge | 1 | none | 0 | acc | ↑ | 0.4002 | ± | 0.0143 |
| none | 0 | acc_norm | ↑ | 0.4249 | ± | 0.0144 | ||
| gsm8k | 3 | flexible-extract | 5 | exact_match | ↑ | 0.5739 | ± | 0.0136 |
| strict-match | 5 | exact_match | ↑ | 0.5732 | ± | 0.0136 | ||
| hellaswag | 1 | none | 0 | acc | ↑ | 0.4865 | ± | 0.0050 |
| none | 0 | acc_norm | ↑ | 0.6512 | ± | 0.0048 | ||
| piqa | 1 | none | 0 | acc | ↑ | 0.7508 | ± | 0.0101 |
| none | 0 | acc_norm | ↑ | 0.7573 | ± | 0.0100 | ||
| sciq | 1 | none | 0 | acc | ↑ | 0.9510 | ± | 0.0068 |
| none | 0 | acc_norm | ↑ | 0.9420 | ± | 0.0074 | ||
| truthfulqa_gen | 3 | none | 0 | bleu_acc | ↑ | 0.4002 | ± | 0.0172 |
| none | 0 | bleu_diff | ↑ | -0.8082 | ± | 1.0249 | ||
| none | 0 | bleu_max | ↑ | 28.4926 | ± | 0.9598 | ||
| none | 0 | rouge1_acc | ↑ | 0.3721 | ± | 0.0169 | ||
| none | 0 | rouge1_diff | ↑ | -3.0804 | ± | 1.1549 | ||
| none | 0 | rouge1_max | ↑ | 51.4182 | ± | 0.9595 | ||
| none | 0 | rouge2_acc | ↑ | 0.3293 | ± | 0.0165 | ||
| none | 0 | rouge2_diff | ↑ | -3.5718 | ± | 1.2898 | ||
| none | 0 | rouge2_max | ↑ | 36.6259 | ± | 1.1000 | ||
| none | 0 | rougeL_acc | ↑ | 0.3905 | ± | 0.0171 | ||
| none | 0 | rougeL_diff | ↑ | -2.8275 | ± | 1.1563 | ||
| none | 0 | rougeL_max | ↑ | 48.9849 | ± | 0.9754 | ||
| truthfulqa_mc1 | 2 | none | 0 | acc | ↑ | 0.2803 | ± | 0.0157 |
| truthfulqa_mc2 | 3 | none | 0 | acc | ↑ | 0.4372 | ± | 0.0146 |
uv run lm_eval --model hf --model_args pretrained=mrs83/Kurtis-EON1-Hybrid-2B-v0.1.2,trust_remote_code=True,device_map="auto" --tasks hellaswag,piqa,sciq,truthfulqa,arc_challenge,gsm8k --batch_size 16 --apply_chat_template