library_name: transformers
license: other
datasets:
- Locutusque/Collective-Evol-Instruct-v0.1
language:
- en
base_model:
- tiiuae/Falcon3-7B-Base
pipeline_tag: text-generation
Model Card for Model ID
Full model card coming soon. Long story short, the curation method for the dataset used in the training of this language model combines methods from Evol instruct and Amplify instruct. The pipeline takes in a single instruction and turns it into a complex multi turn conversation. The resulting dataset yields very good results. It contains around 1.3k examples.
The full model card will be written and the dataset will be published once other models are finished training and evals are complete.
Currently finished evals
| Tasks | Version | Filter | n-shot | Metric | Value | Stderr | ||
|---|---|---|---|---|---|---|---|---|
| agieval_nous | 0 | none | acc_norm | ↑ | 0.4266 | ± | 0.0095 | |
| - agieval_aqua_rat | 1 | none | 0 | acc | ↑ | 0.3268 | ± | 0.0295 |
| none | 0 | acc_norm | ↑ | 0.3150 | ± | 0.0292 | ||
| - agieval_logiqa_en | 1 | none | 0 | acc | ↑ | 0.3825 | ± | 0.0191 |
| none | 0 | acc_norm | ↑ | 0.3856 | ± | 0.0191 | ||
| - agieval_lsat_ar | 1 | none | 0 | acc | ↑ | 0.2652 | ± | 0.0292 |
| none | 0 | acc_norm | ↑ | 0.2348 | ± | 0.0280 | ||
| - agieval_lsat_lr | 1 | none | 0 | acc | ↑ | 0.4667 | ± | 0.0221 |
| none | 0 | acc_norm | ↑ | 0.4294 | ± | 0.0219 | ||
| - agieval_lsat_rc | 1 | none | 0 | acc | ↑ | 0.5911 | ± | 0.0300 |
| none | 0 | acc_norm | ↑ | 0.5465 | ± | 0.0304 | ||
| - agieval_sat_en | 1 | none | 0 | acc | ↑ | 0.7670 | ± | 0.0295 |
| none | 0 | acc_norm | ↑ | 0.7282 | ± | 0.0311 | ||
| - agieval_sat_en_without_passage | 1 | none | 0 | acc | ↑ | 0.4806 | ± | 0.0349 |
| none | 0 | acc_norm | ↑ | 0.4320 | ± | 0.0346 | ||
| - agieval_sat_math | 1 | none | 0 | acc | ↑ | 0.5091 | ± | 0.0338 |
| none | 0 | acc_norm | ↑ | 0.4364 | ± | 0.0335 |
agieval average acc: 0.4736
| Tasks | Version | Filter | n-shot | Metric | Value | Stderr | ||
|---|---|---|---|---|---|---|---|---|
| gsm8k_cot_llama | 3 | flexible-extract | 8 | exact_match | ↑ | 0.8249 | ± | 0.0105 |
| strict-match | 8 | exact_match | ↑ | 0.8241 | ± | 0.0105 |
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