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Model: anakin87/Llama-3-8b-ita-slerp Source: Original Platform
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README.md
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README.md
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---
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base_model:
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- swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA
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- DeepMount00/Llama-3-8b-Ita
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library_name: transformers
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tags:
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- mergekit
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- merge
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license: llama3
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language:
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- it
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---
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# Llama-3-8b-ita-slerp
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This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
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I tried to merge two of the best Italian LLMs using Mergekit. The results are acceptable, but I could not improve on the best existing model.
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## Evaluation
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For a detailed comparison of model performance, check out the [Leaderboard for Italian Language Models](https://huggingface.co/spaces/FinancialSupport/open_ita_llm_leaderboard).
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Here's a breakdown of the performance metrics:
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| Metric | hellaswag_it acc_norm | arc_it acc_norm | m_mmlu_it 5-shot acc | Average |
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|:----------------------------|:----------------------|:----------------|:---------------------|:--------|
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| **Accuracy Normalized** | 0.6879 | 0.5714 | 0.5732 | 0.6109 |
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## Merge Details
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### Merge Method
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This model was merged using the SLERP merge method.
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### Models Merged
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The following models were included in the merge:
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* [swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA](https://huggingface.co/swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA)
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* [DeepMount00/Llama-3-8b-Ita](https://huggingface.co/DeepMount00/Llama-3-8b-Ita)
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### Configuration
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The following YAML configuration was used to produce this model:
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```yaml
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slices:
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- sources:
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- model: swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA
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layer_range:
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- 0
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- 32
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- model: DeepMount00/Llama-3-8b-Ita
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layer_range:
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- 0
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- 32
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merge_method: slerp
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base_model: swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA
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parameters:
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t:
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- filter: self_attn
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value:
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- 0
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- 0.5
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- 0.3
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- 0.7
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- 1
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- filter: mlp
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value:
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- 1
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- 0.5
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- 0.7
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- 0.3
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- 0
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- value: 0.5
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dtype: bfloat16
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```
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