This is a 32k version of Sao10K/WinterGoddess-1.4x-70B-L2, extended using method discussed here.
Quants
Thanks for GGUF, @Nexesenex!
Benchmarks
NeoEvalPlusN_benchmark
| Test name | WinterGoddess | WinterGoddess-32k |
|---|---|---|
| B | 2 | 2.5 |
| C | 1.5 | 2 |
| D | 3 | 0 |
| S | 2.75 | 1.5 |
| P | 5.5 | 2.25 |
| Total | 14.75 | 8.25 |
Open LLM Leaderboard Evaluation Results
| Model | Average | ARC | HellaSwag | MMLU | TruthfulQA | Winogrande | GSM8K |
|---|---|---|---|---|---|---|---|
| Sao10K/WinterGoddess-1.4x-70B-L2 | 73.23 | 72.78 | 90.11 | 71.12 | 65.76 | 85 | 54.59 |
| ChuckMcSneed/WinterGoddess-1.4x-70b-32k | 69.4 | 71.16 | 89.12 | 66.42 | 63.87 | 82.56 | 43.29 |
| Difference | 3.83 | 1.62 | 0.99 | 4.7 | 1.89 | 2.44 | 11.3 |
Here the losses seem far less brutal than on my bench. It seems that extending with LongLORA kills MMLU and GSM8K performance.
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 69.40 |
| AI2 Reasoning Challenge (25-Shot) | 71.16 |
| HellaSwag (10-Shot) | 89.12 |
| MMLU (5-Shot) | 66.42 |
| TruthfulQA (0-shot) | 63.87 |
| Winogrande (5-shot) | 82.56 |
| GSM8k (5-shot) | 43.29 |
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Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard71.160
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard89.120
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard66.420
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard63.870
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard82.560
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard43.290