llama-3-neural-chat-v2.2-8b
Model Details
Model Description
I fine-tuned llama-3 8B on an approach similar to Intel's neural chat language model. I have slightly modified the data sources so it is stronger in coding, math, and writing. I use both SFT and DPO-Positive. DPO-Positive dramatically improves performance over DPO.
- Developed by: Locutusque
- Model type: Built with Meta Llama 3
- Language(s) (NLP): Many?
- License: Llama 3 license https://huggingface.co/meta-llama/Meta-Llama-3-8B/blob/main/LICENSE
Quants
GGUF: https://huggingface.co/bartowski/llama-3-neural-chat-v2.2-8B-GGUF
ExLlamaV2: https://huggingface.co/bartowski/llama-3-neural-chat-v2.2-8B-exl2
Uses
This model has great performance in writing, coding, and math.
Training Data
Recipe information will be coming soon. This language model's recipe is similar to Intel's Neural Chat.
Direct Use
Conversational AI. This model is also very uncensored, it will respond to pretty much any request regardless of the system prompt, use at your own risk.
Evaluations
Tasks | Version | Filter | n-shot | Metric | Value | Stderr | |
---|---|---|---|---|---|---|---|
truthfulqa_mc2 | 2 | none | 0 | acc | 0.5232 | ± | 0.0151 |
gsm8k | 3 | strict-match | 5 | exact_match | 0.5974 | ± | 0.0135 |
flexible-extract | 5 | exact_match | 0.5974 | ± | 0.0135 | ||
agieval_nous | N/A | none | 0 | acc_norm | 0.3841 | ± | 0.0094 |
none | 0 | acc | 0.3802 | ± | 0.0094 | ||
- agieval_aqua_rat | 1 | none | 0 | acc | 0.2598 | ± | 0.0276 |
none | 0 | acc_norm | 0.2520 | ± | 0.0273 | ||
- agieval_logiqa_en | 1 | none | 0 | acc | 0.3441 | ± | 0.0186 |
none | 0 | acc_norm | 0.3687 | ± | 0.0189 | ||
- agieval_lsat_ar | 1 | none | 0 | acc | 0.2217 | ± | 0.0275 |
none | 0 | acc_norm | 0.2348 | ± | 0.0280 | ||
- agieval_lsat_lr | 1 | none | 0 | acc | 0.3882 | ± | 0.0216 |
none | 0 | acc_norm | 0.3824 | ± | 0.0215 | ||
- agieval_lsat_rc | 1 | none | 0 | acc | 0.4944 | ± | 0.0305 |
none | 0 | acc_norm | 0.5019 | ± | 0.0305 | ||
- agieval_sat_en | 1 | none | 0 | acc | 0.6650 | ± | 0.0330 |
none | 0 | acc_norm | 0.6553 | ± | 0.0332 | ||
- agieval_sat_en_without_passage | 1 | none | 0 | acc | 0.3981 | ± | 0.0342 |
none | 0 | acc_norm | 0.3981 | ± | 0.0342 | ||
- agieval_sat_math | 1 | none | 0 | acc | 0.3500 | ± | 0.0322 |
none | 0 | acc_norm | 0.3318 | ± | 0.0318 |
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