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README.md
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---
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language:
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- ja
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tags:
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- japanese-stablelm
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- causal-lm
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pipeline_tag: text-generation
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base_model: stabilityai/japanese-stablelm-base-gamma-7b
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datasets: argilla/ultrafeedback-binarized-preferences-cleaned
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license: apache-2.0
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extra_gated_fields:
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Name: text
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Email: text
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Country: text
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Organization or Affiliation: text
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I allow Stability AI to contact me about information related to its models and research: checkbox
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---
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# Reproduced Japanese Stable LM Instruct Gamma 7B
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## Model Description
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This is a reproduction of 7B-parameter decoder-only Japanese language model fine-tuned on instruction-following datasets, built on top of the base model [Japanese Stable LM Base Gamma 7B](https://huggingface.co/stabilityai/japanese-stablelm-base-gamma-7b).
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This model is trained with [notus](https://github.com/argilla-io/notus) code base.
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*If you are in search of the official model, please check [Japanese Stable LM Instruct Gamma 7B](https://huggingface.co/stabilityai/japanese-stablelm-instruct-gamma-7b).*
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## Model Details
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### Training Datasets
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- [Japanese translation of the Databricks Dolly-15k dataset](https://huggingface.co/datasets/kunishou/databricks-dolly-15k-ja)
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- [Japanese translation of the subset of the Anthropic HH dataset](https://huggingface.co/datasets/fujiki/japanese_hh-rlhf-49k)
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- [Wikinews](https://ja.wikinews.org/wi) [subset](https://huggingface.co/datasets/fujiki/llm-japanese-dataset_wikinews) of the [izumi-lab/llm-japanese-dataset](https://huggingface.co/datasets/izumi-lab/llm-japanese-dataset)
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### Benchmarks
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The result is evaluated by [Nejumi-leaderboard Neo](https://github.com/wandb/llm-leaderboard/tree/b2723944d4955768cb93c18ffe162a8ff4e88955).
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- llm-jp-eval:
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|AVG |EL |FA |MC |MR |NLI |QA |RC |chabsa_set_f1|jamp_exact_match|janli_exact_match|jcommonsenseqa_exact_match|jemhopqa_char_f1|jnli_exact_match|jsem_exact_match|jsick_exact_match|jsquad_char_f1|niilc_char_f1|
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|------|---|---|----|---|-----|------|------|-------------|----------------|-----------------|--------------------------|----------------|----------------|----------------|-----------------|--------------|-------------|
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|0.1691|0.0|0.0|0.24|0.0|0.286|0.1688|0.4887|0.0 |0.3 |0.56 |0.24 |0.1334 |0.08 |0.28 |0.21 |0.4887 |0.2042 |
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- Japanese Mt-Bench:
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|coding|extraction|humanities|math|reasoning|roleplay|stem|writing|
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|------|----------|----------|----|---------|--------|----|-------|
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|1.3 |1.75 |2.35 |1.45|3.4 |5.8 |4.3 |3.1 |
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- Overall Average: 0.266
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