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---
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license: mit
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pipeline_tag: text-generation
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library_name: transformers
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language: [
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'en', 'am', 'ar', 'as', 'az', 'be', 'bg', 'bn', 'br', 'bs', 'ca', 'cs', 'cy', 'da', 'de', 'el',
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'eo', 'es', 'et', 'eu', 'fa', 'ff', 'fi', 'fr', 'fy', 'ga', 'gd', 'gl', 'gn', 'gu', 'ha', 'he',
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'hi', 'hr', 'ht', 'hu', 'hy', 'id', 'ig', 'is', 'it', 'ja', 'jv', 'ka', 'kk', 'km', 'kn', 'ko',
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'ku', 'ky', 'la', 'lg', 'li', 'ln', 'lo', 'lt', 'lv', 'mg', 'mk', 'ml', 'mn', 'mr', 'ms', 'my',
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'ne', 'nl', 'no', 'ns', 'om', 'or', 'pa', 'pl', 'ps', 'pt', 'qu', 'rm', 'ro', 'ru', 'sa', 'si',
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'sc', 'sd', 'sk', 'sl', 'so', 'sq', 'sr', 'ss', 'su', 'sv', 'sw', 'ta', 'te', 'th', 'tl', 'tn',
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'tr', 'ug', 'uk', 'ur', 'uz', 'vi', 'wo', 'xh', 'yi', 'yo', 'zu',
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]
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datasets:
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- ontocord/fineweb-permissive-multilingual-2m
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- distily/c4_multilingual_1M
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- data-silence/sumnews
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- xu-song/cc100-samples
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- badrex/llm-emoji-dataset
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- fblgit/simple-math
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- Gusarich/math-expressions-1m
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- neuralwork/arxiver
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- christopher/rosetta-code
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- nampdn-ai/tiny-codes
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- JeanKaddour/minipile
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- NousResearch/hermes-function-calling-v1
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- simplescaling/s1K-1.1
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- mlabonne/open-perfectblend
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- allenai/tulu-3-sft-mixture
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- rombodawg/Everything_Instruct_Multilingual
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- open-r1/OpenR1-Math-220k
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- open-thoughts/OpenThoughts-114k
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- cognitivecomputations/dolphin-r1
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- simplescaling/s1K-1.1
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tags:
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- chat
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- core
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- base
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- instruct
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- reason
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---
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# tangled-alpha-0.2-core
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```bash
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time python -B prepare_core_datasets.py
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```
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```
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Progress: 100%|████████| 220/220 [23:15<00:00, 6.34s/it]
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Workers are finished.██| 220/220 [23:15<00:00, 6.34s/it]
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Finished data processing!
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i=0, block_size=8192, chunk_size=16384000, len(dataset)=893355, len(dataset) * block_size=7318364160
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Total number of tokens in the optimized dataset '../core-data-0-8192-2000' is 7318364160
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```
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```bash
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CUDA_VISIBLE_DEVICES=0 CUDA_LAUNCH_BLOCKING=0 PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True litgpt pretrain --config pretrain-core-model.yaml
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```
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```
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Seed set to 23
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Time to instantiate model: 0.32 seconds.
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Total parameters: 217,088,512
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Verifying settings ...
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Measured TFLOPs: 3548.40
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Epoch 1 | iter 256 step 1 | loss train: 11.716, val: n/a | iter time: 1735.26 ms (step) remaining time: 4 days, 11:06:29
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Epoch 1 | iter 512 step 2 | loss train: 11.534, val: n/a | iter time: 1102.77 ms (step) remaining time: 4 days, 2:31:30
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Epoch 1 | iter 768 step 3 | loss train: 11.356, val: n/a | iter time: 1095.87 ms (step) remaining time: 3 days, 23:44:12
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Epoch 1 | iter 1024 step 4 | loss train: 11.162, val: n/a | iter time: 1099.92 ms (step) remaining time: 3 days, 22:18:27
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Epoch 1 | iter 1280 step 5 | loss train: 11.018, val: n/a | iter time: 1096.45 ms (step) remaining time: 3 days, 21:24:35
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Epoch 1 | iter 1536 step 6 | loss train: 10.901, val: n/a | iter time: 1093.65 ms (step) remaining time: 3 days, 20:48:11
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Epoch 1 | iter 1792 step 7 | loss train: 10.850, val: n/a | iter time: 1100.16 ms (step) remaining time: 3 days, 20:22:00
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Epoch 1 | iter 2048 step 8 | loss train: 10.780, val: n/a | iter time: 1092.67 ms (step) remaining time: 3 days, 20:01:57
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Epoch 1 | iter 2304 step 9 | loss train: 10.692, val: n/a | iter time: 1095.77 ms (step) remaining time: 3 days, 19:45:57
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Epoch 1 | iter 2560 step 10 | loss train: 10.678, val: n/a | iter time: 1092.12 ms (step) remaining time: 3 days, 19:32:43
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Epoch 1 | iter 2816 step 11 | loss train: 10.619, val: n/a | iter time: 1094.44 ms (step) remaining time: 3 days, 19:21:32
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Epoch 1 | iter 3072 step 12 | loss train: 10.588, val: n/a | iter time: 1102.51 ms (step) remaining time: 3 days, 19:12:30
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Epoch 1 | iter 3328 step 13 | loss train: 10.514, val: n/a | iter time: 1095.57 ms (step) remaining time: 3 days, 19:04:07
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Epoch 1 | iter 3584 step 14 | loss train: 10.472, val: n/a | iter time: 1104.00 ms (step) remaining time: 3 days, 18:56:56
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Epoch 1 | iter 3840 step 15 | loss train: 10.431, val: n/a | iter time: 1096.00 ms (step) remaining time: 3 days, 18:50:21
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Epoch 1 | iter 4096 step 16 | loss train: 10.392, val: n/a | iter time: 1098.34 ms (step) remaining time: 3 days, 18:44:25
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Epoch 1 | iter 4352 step 17 | loss train: 10.360, val: n/a | iter time: 1106.53 ms (step) remaining time: 3 days, 18:38:58
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Epoch 1 | iter 4608 step 18 | loss train: 10.329, val: n/a | iter time: 1084.95 ms (step) remaining time: 3 days, 18:33:58
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Epoch 1 | iter 4864 step 19 | loss train: 10.296, val: n/a | iter time: 1096.22 ms (step) remaining time: 3 days, 18:29:12
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Epoch 1 | iter 5120 step 20 | loss train: 10.236, val: n/a | iter time: 1093.39 ms (step) remaining time: 3 days, 18:24:51
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# ...
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```
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Backup `wandb`:
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```bash
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mv wandb wandb-pretrain-core
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```
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Chat with model:
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```bash
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CUDA_VISIBLE_DEVICES=0 CUDA_LAUNCH_BLOCKING=0 PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True litgpt chat ../out/pretrain-core/final
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```
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```bash
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CUDA_VISIBLE_DEVICES=0 CUDA_LAUNCH_BLOCKING=0 PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True time litgpt evaluate --tasks 'leaderboard' --out_dir '../evaluate/pretrain-core/leaderboard/' --batch_size 1 --dtype 'bfloat16' '../out/pretrain-core/final'
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```
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```
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# ...
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```
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