TinyLlama 1.1B https://github.com/jzhang38/TinyLlama The TinyLlama project aims to pretrain a 1.1B Llama model on 3 trillion tokens . With some proper optimization, we can achieve this within a span of "just" 90 days using 16 A100 40G GPUs 🚀🚀. The training has started on 2023 09 01. We adopted exactly the same architecture and tokenizer as Llama 2. This means TinyLlama can be plugged and played in many open source projects built upon Llama. Besides, TinyLlama is compact with only 1.1B parameters. This compactness allows it to cater to a multitude of applications demanding a restricted computation and memory footprint. This Collection This collection contains all checkpoints after the 1T fix. Branch name indicates the step and number of tokens seen. Eval Model Pretrain Tokens HellaSwag Obqa WinoGrande ARC c ARC e boolq piqa avg Pythia 1.0B 300B 47.16 31.40 53.43 27.05 48.99 60.83 69.21 48.30 TinyLlama 1.1B intermediate step 50K 104b 103B 43.50 29.80 53.28 24.32 44.91 59.66 67.30 46.11 TinyLlama 1.1B intermediate step 240k 503b 503B 49.56 31.40 55.80 26.54 48.32 56.91 69.42 48.28 TinyLlama 1.1B intermediate step 480k 1007B 1007B 52.54 33.40 55.96 27.82 52.36 59.54 69.91 50.22 TinyL…
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