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---
license: mit
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:
# core - base
- ontocord/fineweb-permissive-multilingual-2m
- distily/c4_multilingual_1M
- data-silence/sumnews
- xu-song/cc100-samples
- badrex/llm-emoji-dataset
- fblgit/simple-math
- Gusarich/math-expressions-1m
- neuralwork/arxiver
- christopher/rosetta-code
- nampdn-ai/tiny-codes
- JeanKaddour/minipile
# core - instruct
- NousResearch/hermes-function-calling-v1
- simplescaling/s1K-1.1
# base - instruct
- mlabonne/open-perfectblend
- allenai/tulu-3-sft-mixture
- rombodawg/Everything_Instruct_Multilingual
# base - reason
- open-r1/OpenR1-Math-220k
- open-thoughts/OpenThoughts-114k
- cognitivecomputations/dolphin-r1
- simplescaling/s1K-1.1
tags:
- chat
- core
- base
- instruct
- reason
---
# tangled-alpha-0.1-core
```bash
time python -B prepare_core_datasets.py
```
```
Progress: 100%|████████| 220/220 [23:15<00:00, 6.34s/it]
Workers are finished.██| 220/220 [23:15<00:00, 6.34s/it]
Finished data processing!
i=0, block_size=8192, chunk_size=16384000, len(dataset)=893355, len(dataset) * block_size=7318364160
Total number of tokens in the optimized dataset '../core-data-0-8192-2000' is 7318364160
```
```bash
CUDA_VISIBLE_DEVICES=0 CUDA_LAUNCH_BLOCKING=0 PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True litgpt pretrain --config pretrain-core-model.yaml
```
```
Seed set to 23
Time to instantiate model: 0.23 seconds.
Total parameters: 138,084,864
Verifying settings ...
Measured TFLOPs: 6972.54
Epoch 1 | iter 256 step 1 | loss train: 10.530, val: n/a | iter time: 3230.47 ms (step) remaining time: 3 days, 5:34:13
Epoch 1 | iter 512 step 2 | loss train: 10.520, val: n/a | iter time: 589.19 ms (step) remaining time: 3 days, 0:40:40
Epoch 1 | iter 768 step 3 | loss train: 10.485, val: n/a | iter time: 591.81 ms (step) remaining time: 2 days, 23:01:54
Epoch 1 | iter 1024 step 4 | loss train: 10.447, val: n/a | iter time: 589.35 ms (step) remaining time: 2 days, 22:11:32
Epoch 1 | iter 1280 step 5 | loss train: 10.350, val: n/a | iter time: 589.38 ms (step) remaining time: 2 days, 21:40:13
Epoch 1 | iter 1536 step 6 | loss train: 10.241, val: n/a | iter time: 593.75 ms (step) remaining time: 2 days, 21:18:19
Epoch 1 | iter 1792 step 7 | loss train: 10.134, val: n/a | iter time: 592.92 ms (step) remaining time: 2 days, 21:01:58
Epoch 1 | iter 2048 step 8 | loss train: 10.049, val: n/a | iter time: 590.74 ms (step) remaining time: 2 days, 20:49:12
Epoch 1 | iter 2304 step 9 | loss train: 9.869, val: n/a | iter time: 594.27 ms (step) remaining time: 2 days, 20:39:10
Epoch 1 | iter 2560 step 10 | loss train: 9.771, val: n/a | iter time: 590.04 ms (step) remaining time: 2 days, 20:30:14
Epoch 1 | iter 2816 step 11 | loss train: 9.643, val: n/a | iter time: 588.32 ms (step) remaining time: 2 days, 20:22:22
Epoch 1 | iter 3072 step 12 | loss train: 9.557, val: n/a | iter time: 588.95 ms (step) remaining time: 2 days, 20:15:26
Epoch 1 | iter 3328 step 13 | loss train: 9.487, val: n/a | iter time: 589.32 ms (step) remaining time: 2 days, 20:09:05
Epoch 1 | iter 3584 step 14 | loss train: 9.413, val: n/a | iter time: 588.95 ms (step) remaining time: 2 days, 20:03:24
Epoch 1 | iter 3840 step 15 | loss train: 9.322, val: n/a | iter time: 591.62 ms (step) remaining time: 2 days, 19:58:18
Epoch 1 | iter 4096 step 16 | loss train: 9.241, val: n/a | iter time: 593.65 ms (step) remaining time: 2 days, 19:53:30
Epoch 1 | iter 4352 step 17 | loss train: 9.163, val: n/a | iter time: 593.89 ms (step) remaining time: 2 days, 19:49:00
Epoch 1 | iter 4608 step 18 | loss train: 9.122, val: n/a | iter time: 590.63 ms (step) remaining time: 2 days, 19:44:42
Epoch 1 | iter 4864 step 19 | loss train: 9.077, val: n/a | iter time: 590.87 ms (step) remaining time: 2 days, 19:40:47
Epoch 1 | iter 5120 step 20 | loss train: 9.018, val: n/a | iter time: 588.44 ms (step) remaining time: 2 days, 19:36:59
# ...
```
Backup `wandb`:
```bash
mv wandb wandb-pretrain-core
```
Chat with model:
```bash
CUDA_VISIBLE_DEVICES=0 CUDA_LAUNCH_BLOCKING=0 PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True litgpt chat ../out/pretrain-core/final
```
```bash
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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