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update doc.
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README.md
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value: 87.15717597277224
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- type: max_f1
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value: 79.71815316150567
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value: 87.15717597277224
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- type: max_f1
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value: 79.71815316150567
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---
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## Model Details:
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This embedding model is a fine-tuned 10.7B parameter LLM on the Intel Gaudi 2 processor using the [upstage/SOLAR-10.7B-v1.0](https://huggingface.co/upstage/SOLAR-10.7B-v1.0).
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## Date
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July, 2024
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## Training Details
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Two stage training:
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- General Text Embedding Training
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- Specific domains Emebedding Training
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More technical details will be updated later.
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## Evaluation
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The results of (MTEB)[https://huggingface.co/spaces/mteb/leaderboard] (English):
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| Model Name | MTEB(56) ||
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|:----:|:---------:|:----------:|
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| [bge-base-en-1.5](https://huggingface.co/BAAI/bge-base-en-v1.5) | 64.23 |
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| [bge-large-en-1.5](https://huggingface.co/BAAI/bge-large-en-v1.5) | 63.55 |
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| [gte-large-en-v1.5](https://huggingface.co/Alibaba-NLP/gte-large-en-v1.5) | 65.39 |
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| [gte-base-en-v1.5](https://huggingface.co/Alibaba-NLP/gte-large-en-v1.5) | 64.11 |
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| [mxbai-embed-large-v1](https://huggingface.co/mixedbread-ai/mxbai-embed-large-v1) | 64.68 |
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| [multilingual-e5-base](https://huggingface.co/intfloat/multilingual-e5-base) | 59.45 |
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| [multilingual-e5-large](https://huggingface.co/intfloat/multilingual-e5-large) | 61.50 |
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| [e5-mistral-7b-instruct](https://huggingface.co/intfloat/e5-mistral-7b-instruct) | 66.63 |
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| [gte-Qwen1.5-7B-instruct](https://huggingface.co/Alibaba-NLP/gte-Qwen1.5-7B-instruct) | 67.34 |
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| [NV-Embed-v1](https://huggingface.co/nvidia/NV-Embed-v1) | 69.32 |
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| [**neural-embedding-v1**](https://huggingface.co/Intel/neural-embedding-v1) | **69.94** |
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