TinyLlama-1.1B-intermediate-step-1431k-3T

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README(From Huggingface)

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language:

• en license: apache-2.0 datasets:

• cerebras/SlimPajama-627B

• bigcode/starcoderdata model-index:

• name: TinyLlama-1.1B-intermediate-step-1431k-3T results:

  • task: type: text-generation name: Text Generation dataset: name: AI2 Reasoning Challenge (25-Shot) type: ai2_arc config: ARC-Challenge split: test args: num_few_shot: 25 metrics:

    • type: acc_norm value: 33.87 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T name: Open LLM Leaderboard

  • task: type: text-generation name: Text Generation dataset: name: HellaSwag (10-Shot) type: hellaswag split: validation args: num_few_shot: 10 metrics:

    • type: acc_norm value: 60.31 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T name: Open LLM Leaderboard

  • task: type: text-generation name: Text Generation dataset: name: MMLU (5-Shot) type: cais/mmlu config: all split: test args: num_few_shot: 5 metrics:

    • type: acc value: 26.04 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T name: Open LLM Leaderboard

  • task: type: text-generation name: Text Generation dataset: name: TruthfulQA (0-shot) type: truthful_qa config: multiple_choice split: validation args: num_few_shot: 0 metrics:

    • type: mc2 value: 37.32 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T name: Open LLM Leaderboard

  • task: type: text-generation name: Text Generation dataset: name: Winogrande (5-shot) type: winogrande config: winogrande_xl split: validation args: num_few_shot: 5 metrics:

    • type: acc value: 59.51 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T name: Open LLM Leaderboard

  • task: type: text-generation name: Text Generation dataset: name: GSM8k (5-shot) type: gsm8k config: main split: test args: num_few_shot: 5 metrics:

    • type: acc value: 1.44 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T name: Open LLM Leaderboard

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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
TinyLlama-1.1B-intermediate-step-715k-1.5T	1.5T	53.68	35.20	58.33	29.18	51.89	59.08	71.65	51.29
TinyLlama-1.1B-intermediate-step-955k-2T	2T	54.63	33.40	56.83	28.07	54.67	63.21	70.67	51.64
TinyLlama-1.1B-intermediate-step-1195k-2.5T	2.5T	58.96	34.40	58.72	31.91	56.78	63.21	73.07	53.86
TinyLlama-1.1B-intermediate-step-1431k-3T	3T	59.20	36.00	59.12	30.12	55.25	57.83	73.29	52.99
# Open LLM Leaderboard Evaluation Results
Detailed results can be found here

Metric	Value
Avg.	36.42
AI2 Reasoning Challenge (25-Shot)	33.87
HellaSwag (10-Shot)	60.31
MMLU (5-Shot)	26.04
TruthfulQA (0-shot)	37.32
Winogrande (5-shot)	59.51
GSM8k (5-shot)	1.44

Model Files

• README.md (5.7 KB)

• config.json (554.0 B)

• generation_config.json (129.0 B)

• model.safetensors (4.1 GB)

• special_tokens_map.json (414.0 B)

• tokenizer.json (1.8 MB)

• tokenizer.model (488.0 KB)

• tokenizer_config.json (776.0 B)

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