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---
license: apache-2.0
pipeline_tag: text-generation
library_name: transformers
language: [
'en', 'am', 'ar', 'as', 'az', 'be', 'bg', 'bn', 'br', 'bs', 'ca', 'cs', 'cy', 'da', 'de', 'el',
'eo', 'es', 'et', 'eu', 'fa', 'ff', 'fi', 'fr', 'fy', 'ga', 'gd', 'gl', 'gn', 'gu', 'ha', 'he',
'hi', 'hr', 'ht', 'hu', 'hy', 'id', 'ig', 'is', 'it', 'ja', 'jv', 'ka', 'kk', 'km', 'kn', 'ko',
'ku', 'ky', 'la', 'lg', 'li', 'ln', 'lo', 'lt', 'lv', 'mg', 'mk', 'ml', 'mn', 'mr', 'ms', 'my',
'ne', 'nl', 'no', 'ns', 'om', 'or', 'pa', 'pl', 'ps', 'pt', 'qu', 'rm', 'ro', 'ru', 'sa', 'si',
'sc', 'sd', 'sk', 'sl', 'so', 'sq', 'sr', 'ss', 'su', 'sv', 'sw', 'ta', 'te', 'th', 'tl', 'tn',
'tr', 'ug', 'uk', 'ur', 'uz', 'vi', 'wo', 'xh', 'yi', 'yo', 'zu',
]
datasets: [
'yahma/alpaca-cleaned',
'gbharti/wealth-alpaca_lora',
'databricks/databricks-dolly-15k',
'VMware/open-instruct',
'saillab/taco-datasets',
'xu-song/cc100-samples',
'jordiclive/wikipedia-summary-dataset',
'bigcode/the-stack-smol-xs',
'm-a-p/CodeFeedback-Filtered-Instruction',
'jtatman/python-code-dataset-500k',
'iamtarun/python_code_instructions_18k_alpaca',
'HuggingFaceH4/CodeAlpaca_20K',
'cognitivecomputations/dolphin-coder',
'fblgit/simple-math',
'gair-prox/open-web-math-pro',
'rvv-karma/Math-QA',
'ajibawa-2023/Maths-College',
'microsoft/orca-math-word-problems-200k',
'meta-math/MetaMathQA',
'TIGER-Lab/MathInstruct',
'TIGER-Lab/WebInstructSub',
'SkunkworksAI/reasoning-0.01',
'KingNish/reasoning-base-20k',
'Magpie-Align/Magpie-Reasoning-150K',
'thesven/gsm8k-reasoning',
'AlgorithmicResearchGroup/math_reasoning_autoformalization_track',
'badrex/llm-emoji-dataset',
]
tags:
- litgpt
- litdata
---
# tangled-llama-t-32k-base-v0.1
A pretrained language model based on the Llama model with about **25M** parameters. This model has been trained on **22.1B** (`22,111,299,936`) tokens from more than **3.6M** (`3,597,088`) dataset rows.
This model **isn't** designed for immediate use but rather for Continued Pretraining and Finetuning on a downstream task. While it can handle a context length of up to **128K** (`131,072`) tokens, it was pretrained with sequences of **2K** (`2048`) tokens.
The objective is to streamline the cognitive or reasoning core, eliminating any redundant knowledge from the model.
[loss, val_loss](https://api.wandb.ai/links/mtasic85/t66yvgeh)
[val_ppl](https://api.wandb.ai/links/mtasic85/osr62qqd)
[epoch](https://api.wandb.ai/links/mtasic85/pw0ilz5s)
[learning_rate](https://api.wandb.ai/links/mtasic85/867ueoyx)
## lm-evaluation-harness
```bash
litgpt evaluate --tasks 'hellaswag,gsm8k,truthfulqa_mc2,mmlu,winogrande,arc_challenge' --out_dir 'evaluate-quick/' --batch_size 4 --dtype 'bfloat16' out/pretrain/final/
```
Tasks |Version| Filter |n-shot| Metric | |Value | |Stderr|
|---------------------------------------|------:|----------------|-----:|-----------|---|-----:|---|-----:|
|arc_challenge | 1|none | 0|acc |↑ |0.1971|± |0.0116|
| | |none | 0|acc_norm |↑ |0.2423|± |0.0125|
|gsm8k | 3|flexible-extract| 5|exact_match|↑ |0.0099|± |0.0027|
| | |strict-match | 5|exact_match|↑ |0.0000|± |0.0000|
|hellaswag | 1|none | 0|acc |↑ |0.2608|± |0.0044|
| | |none | 0|acc_norm |↑ |0.2665|± |0.0044|
|mmlu | 2|none | |acc |↑ |0.2451|± |0.0036|
| - humanities | 2|none | |acc |↑ |0.2470|± |0.0063|
| - formal_logic | 1|none | 0|acc |↑ |0.3254|± |0.0419|
| - high_school_european_history | 1|none | 0|acc |↑ |0.2545|± |0.0340|
| - high_school_us_history | 1|none | 0|acc |↑ |0.2745|± |0.0313|
| - high_school_world_history | 1|none | 0|acc |↑ |0.2194|± |0.0269|
| - international_law | 1|none | 0|acc |↑ |0.2231|± |0.0380|
| - jurisprudence | 1|none | 0|acc |↑ |0.2685|± |0.0428|
| - logical_fallacies | 1|none | 0|acc |↑ |0.2025|± |0.0316|
| - moral_disputes | 1|none | 0|acc |↑ |0.2457|± |0.0232|
| - moral_scenarios | 1|none | 0|acc |↑ |0.2670|± |0.0148|
| - philosophy | 1|none | 0|acc |↑ |0.1865|± |0.0221|
| - prehistory | 1|none | 0|acc |↑ |0.2500|± |0.0241|
| - professional_law | 1|none | 0|acc |↑ |0.2523|± |0.0111|
| - world_religions | 1|none | 0|acc |↑ |0.1871|± |0.0299|
| - other | 2|none | |acc |↑ |0.2456|± |0.0077|
| - business_ethics | 1|none | 0|acc |↑ |0.3400|± |0.0476|
| - clinical_knowledge | 1|none | 0|acc |↑ |0.2113|± |0.0251|
| - college_medicine | 1|none | 0|acc |↑ |0.2543|± |0.0332|
| - global_facts | 1|none | 0|acc |↑ |0.1800|± |0.0386|
| - human_aging | 1|none | 0|acc |↑ |0.1749|± |0.0255|
| - management | 1|none | 0|acc |↑ |0.3398|± |0.0469|
| - marketing | 1|none | 0|acc |↑ |0.2479|± |0.0283|
| - medical_genetics | 1|none | 0|acc |↑ |0.3100|± |0.0465|
| - miscellaneous | 1|none | 0|acc |↑ |0.2171|± |0.0147|
| - nutrition | 1|none | 0|acc |↑ |0.2647|± |0.0253|
| - professional_accounting | 1|none | 0|acc |↑ |0.2270|± |0.0250|
| - professional_medicine | 1|none | 0|acc |↑ |0.2978|± |0.0278|
| - virology | 1|none | 0|acc |↑ |0.3133|± |0.0361|
| - social sciences | 2|none | |acc |↑ |0.2584|± |0.0079|
| - econometrics | 1|none | 0|acc |↑ |0.2193|± |0.0389|
| - high_school_geography | 1|none | 0|acc |↑ |0.2677|± |0.0315|
| - high_school_government_and_politics| 1|none | 0|acc |↑ |0.2435|± |0.0310|
| - high_school_macroeconomics | 1|none | 0|acc |↑ |0.2538|± |0.0221|
| - high_school_microeconomics | 1|none | 0|acc |↑ |0.2647|± |0.0287|
| - high_school_psychology | 1|none | 0|acc |↑ |0.2679|± |0.0190|
| - human_sexuality | 1|none | 0|acc |↑ |0.3435|± |0.0416|
| - professional_psychology | 1|none | 0|acc |↑ |0.2190|± |0.0167|
| - public_relations | 1|none | 0|acc |↑ |0.2091|± |0.0390|
| - security_studies | 1|none | 0|acc |↑ |0.2980|± |0.0293|
| - sociology | 1|none | 0|acc |↑ |0.2836|± |0.0319|
| - us_foreign_policy | 1|none | 0|acc |↑ |0.3000|± |0.0461|
| - stem | 2|none | |acc |↑ |0.2287|± |0.0075|
| - abstract_algebra | 1|none | 0|acc |↑ |0.2100|± |0.0409|
| - anatomy | 1|none | 0|acc |↑ |0.2000|± |0.0346|
| - astronomy | 1|none | 0|acc |↑ |0.2434|± |0.0349|
| - college_biology | 1|none | 0|acc |↑ |0.3333|± |0.0394|
| - college_chemistry | 1|none | 0|acc |↑ |0.3000|± |0.0461|
| - college_computer_science | 1|none | 0|acc |↑ |0.2600|± |0.0441|
| - college_mathematics | 1|none | 0|acc |↑ |0.3100|± |0.0465|
| - college_physics | 1|none | 0|acc |↑ |0.2353|± |0.0422|
| - computer_security | 1|none | 0|acc |↑ |0.2300|± |0.0423|
| - conceptual_physics | 1|none | 0|acc |↑ |0.2085|± |0.0266|
| - electrical_engineering | 1|none | 0|acc |↑ |0.2621|± |0.0366|
| - elementary_mathematics | 1|none | 0|acc |↑ |0.2011|± |0.0206|
| - high_school_biology | 1|none | 0|acc |↑ |0.2097|± |0.0232|
| - high_school_chemistry | 1|none | 0|acc |↑ |0.2217|± |0.0292|
| - high_school_computer_science | 1|none | 0|acc |↑ |0.2300|± |0.0423|
| - high_school_mathematics | 1|none | 0|acc |↑ |0.1926|± |0.0240|
| - high_school_physics | 1|none | 0|acc |↑ |0.2318|± |0.0345|
| - high_school_statistics | 1|none | 0|acc |↑ |0.1806|± |0.0262|
| - machine_learning | 1|none | 0|acc |↑ |0.2857|± |0.0429|
|truthfulqa_mc2 | 2|none | 0|acc |↑ |0.4880|± |0.0161|
|winogrande | 1|none | 0|acc |↑ |0.5185|± |0.0140|
| Groups |Version|Filter|n-shot|Metric| |Value | |Stderr|
|------------------|------:|------|------|------|---|-----:|---|-----:|
|mmlu | 2|none | |acc |↑ |0.2451|± |0.0036|
| - humanities | 2|none | |acc |↑ |0.2470|± |0.0063|
| - other | 2|none | |acc |↑ |0.2456|± |0.0077|
| - social sciences| 2|none | |acc |↑ |0.2584|± |0.0079|
| - stem | 2|none | |acc |↑ |0.2287|± |0.0075|
```bash
litgpt evaluate --tasks 'leaderboard' --out_dir 'evaluate-leaderboard/' --batch_size 4 --dtype 'bfloat16' out/pretrain/final/
```
| Tasks |Version|Filter|n-shot| Metric | |Value | |Stderr|
|-----------------------------------------------------------|-------|------|-----:|-----------------------|---|-----:|---|------|
|leaderboard | N/A| | | | | | | |
| - leaderboard_bbh | N/A| | | | | | | |
| - leaderboard_bbh_boolean_expressions | 1|none | 3|acc_norm |↑ |0.4600|± |0.0316|
| - leaderboard_bbh_causal_judgement | 1|none | 3|acc_norm |↑ |0.5027|± |0.0367|
| - leaderboard_bbh_date_understanding | 1|none | 3|acc_norm |↑ |0.1720|± |0.0239|
| - leaderboard_bbh_disambiguation_qa | 1|none | 3|acc_norm |↑ |0.2960|± |0.0289|
| - leaderboard_bbh_formal_fallacies | 1|none | 3|acc_norm |↑ |0.4880|± |0.0317|
| - leaderboard_bbh_geometric_shapes | 1|none | 3|acc_norm |↑ |0.0000|± | 0|
| - leaderboard_bbh_hyperbaton | 1|none | 3|acc_norm |↑ |0.5160|± |0.0317|
| - leaderboard_bbh_logical_deduction_five_objects | 1|none | 3|acc_norm |↑ |0.2000|± |0.0253|
| - leaderboard_bbh_logical_deduction_seven_objects | 1|none | 3|acc_norm |↑ |0.1480|± |0.0225|
| - leaderboard_bbh_logical_deduction_three_objects | 1|none | 3|acc_norm |↑ |0.3160|± |0.0295|
| - leaderboard_bbh_movie_recommendation | 1|none | 3|acc_norm |↑ |0.2360|± |0.0269|
| - leaderboard_bbh_navigate | 1|none | 3|acc_norm |↑ |0.4680|± |0.0316|
| - leaderboard_bbh_object_counting | 1|none | 3|acc_norm |↑ |0.0480|± |0.0135|
| - leaderboard_bbh_penguins_in_a_table | 1|none | 3|acc_norm |↑ |0.1918|± |0.0327|
| - leaderboard_bbh_reasoning_about_colored_objects | 1|none | 3|acc_norm |↑ |0.1440|± |0.0222|
| - leaderboard_bbh_ruin_names | 1|none | 3|acc_norm |↑ |0.2360|± |0.0269|
| - leaderboard_bbh_salient_translation_error_detection | 1|none | 3|acc_norm |↑ |0.1360|± |0.0217|
| - leaderboard_bbh_snarks | 1|none | 3|acc_norm |↑ |0.5225|± |0.0375|
| - leaderboard_bbh_sports_understanding | 1|none | 3|acc_norm |↑ |0.4560|± |0.0316|
| - leaderboard_bbh_temporal_sequences | 1|none | 3|acc_norm |↑ |0.2960|± |0.0289|
| - leaderboard_bbh_tracking_shuffled_objects_five_objects | 1|none | 3|acc_norm |↑ |0.2120|± |0.0259|
| - leaderboard_bbh_tracking_shuffled_objects_seven_objects| 1|none | 3|acc_norm |↑ |0.1840|± |0.0246|
| - leaderboard_bbh_tracking_shuffled_objects_three_objects| 1|none | 3|acc_norm |↑ |0.3160|± |0.0295|
| - leaderboard_bbh_web_of_lies | 1|none | 3|acc_norm |↑ |0.5200|± |0.0317|
| - leaderboard_gpqa | N/A| | | | | | | |
| - leaderboard_gpqa_diamond | 1|none | 0|acc_norm |↑ |0.2172|± |0.0294|
| - leaderboard_gpqa_extended | 1|none | 0|acc_norm |↑ |0.2454|± |0.0184|
| - leaderboard_gpqa_main | 1|none | 0|acc_norm |↑ |0.2478|± |0.0204|
| - leaderboard_ifeval | 3|none | 0|inst_level_loose_acc |↑ |0.1727|± | N/A|
| | |none | 0|inst_level_strict_acc |↑ |0.1559|± | N/A|
| | |none | 0|prompt_level_loose_acc |↑ |0.0832|± |0.0119|
| | |none | 0|prompt_level_strict_acc|↑ |0.0795|± |0.0116|
| - leaderboard_math_hard | N/A| | | | | | | |
| - leaderboard_math_algebra_hard | 1|none | 4|exact_match |↑ |0.0000|± | 0|
| - leaderboard_math_counting_and_prob_hard | 1|none | 4|exact_match |↑ |0.0000|± | 0|
| - leaderboard_math_geometry_hard | 1|none | 4|exact_match |↑ |0.0000|± | 0|
| - leaderboard_math_intermediate_algebra_hard | 1|none | 4|exact_match |↑ |0.0000|± | 0|
| - leaderboard_math_num_theory_hard | 1|none | 4|exact_match |↑ |0.0000|± | 0|
| - leaderboard_math_prealgebra_hard | 1|none | 4|exact_match |↑ |0.0000|± | 0|
| - leaderboard_math_precalculus_hard | 1|none | 4|exact_match |↑ |0.0000|± | 0|
| - leaderboard_mmlu_pro | 0.1|none | 5|acc |↑ |0.1135|± |0.0029|
| - leaderboard_musr | N/A| | | | | | | |
| - leaderboard_musr_murder_mysteries | 1|none | 0|acc_norm |↑ |0.5240|± |0.0316|
| - leaderboard_musr_object_placements | 1|none | 0|acc_norm |↑ |0.2734|± |0.0279|
| - leaderboard_musr_team_allocation | 1|none | 0|acc_norm |↑ |0.3000|± |0.0290|
```bash
litgpt evaluate --tasks 'bbh_zeroshot,bbh_fewshot,bbh_cot_fewshot,bbh_cot_zeroshot' --out_dir 'evaluate-bigbenchhard/' --batch_size 4 --dtype 'bfloat16' out/pretrain/final/
```
```bash
litgpt evaluate --tasks 'mmlu,mmlu_pro' --out_dir 'evaluate-mmlu/' --batch_size 4 --dtype 'bfloat16' out/pretrain/final/
```
```bash
litgpt evaluate --tasks 'arc_challenge,boolq,gpqa,hellaswag,openbookqa,piqa,truthfulqa_mc2,winogrande' --out_dir 'evaluate-reasoning/' --batch_size 4 --dtype 'bfloat16' out/pretrain/final/
```
```bash
litgpt evaluate --tasks 'mmlu_multilingual,mgsm' --out_dir 'evaluate-multilinguals/' --batch_size 4 --dtype 'bfloat16' out/pretrain/final/
```
```bash
litgpt evaluate --tasks 'gsm8k,mathqa' --out_dir 'evaluate-math/' --batch_size 4 --dtype 'bfloat16' out/pretrain/final/
```
|Tasks |Version| Filter |n-shot| Metric | |Value | |Stderr|
|------|------:|----------------|-----:|-----------|---|-----:|---|-----:|
|gsm8k | 3|flexible-extract| 5|exact_match|↑ |0.0099|± |0.0027|
| | |strict-match | 5|exact_match|↑ |0.0000|± |0.0000|
|mathqa| 1|none | 0|acc |↑ |0.2121|± |0.0075|
| | |none | 0|acc_norm |↑ |0.2114|± |0.0075|
```bash
litgpt evaluate --tasks 'wikitext,qasper' --out_dir 'evaluate-long/' --batch_size 4 --dtype 'bfloat16' out/pretrain/final/
```
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