初始化项目，由ModelHub XC社区提供模型
Model: m-a-p/OpenLLaMA-Reproduce-2041.21B Source: Original Platform
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README.md
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README.md
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# OpenLLaMA 7Bv2 Model Card
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## Model Description
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OpenLLaMA 7Bv2 is a cutting-edge language model, trained with a focus on delivering high-quality, contextually relevant text predictions. It leverages a diverse composite dataset that includes web-crawled data, scholarly articles, and a wide range of literature and question-answer pairs to ensure broad domain coverage and applicability.
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## Training Data
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The model was trained on a composite dataset that includes:
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- Falcon refined-web dataset
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- starcoder datasets
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- Contributions from Wikipedia for encyclopedic knowledge
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- Academic papers from arXiv for scientific understanding
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- A vast collection of books spanning multiple genres
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- Stack Exchange data curated by RedPajama
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## Training Procedure
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- **Learning Rate:** Utilized a maximum learning rate of 3e-4 and a minimum learning rate of 3e-5.
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- **Batch Size:** Employed a batch size of 4 million tokens, optimizing the training process for both efficiency and performance.
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- **Learning Rate Scheduler:** The model's learning rate scheduling closely follows the strategy used in Llama2, ensuring gradual adjustments for optimal convergence.
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config.json
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"architectures": [
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"LlamaForCausalLM"
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],
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"model_type": "llama",
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}
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{"framework": "pytorch", "task": "text-generation", "allow_remote": true}
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3
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Normal file
3
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1
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||||
Reference in New Issue
Block a user