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Mistral Ei Oc Unstructured Train by Holmeister

 »  All LLMs  »  Holmeister  »  Mistral Ei Oc Unstructured Train   URL Share it on

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  Adapter Base model:adapter:mistralai/m... Base model:mistralai/mistral-7...   Finetuned   Generated from trainer   Llama-factory   Lora   Peft   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/Holmeister/Mistral_ei_oc_unstructured_train 

Mistral Ei Oc Unstructured Train Benchmarks

LLME Score: 0.17579
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mistral Ei Oc Unstructured Train (Holmeister/Mistral_ei_oc_unstructured_train)

Mistral Ei Oc Unstructured Train Parameters and Internals

Model Type 
LLaMA-factory, LoRA
Additional Notes 
Training hyperparameters: learning_rate: 0.0003, train_batch_size: 32, eval_batch_size: 8, seed: 42, gradient_accumulation_steps: 8, total_train_batch_size: 256, optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08, lr_scheduler_type: cosine, num_epochs: 3.0
Training Details 
Data Sources:
emollms_ei_oc_unstructured dataset
Methodology:
fine-tuning
LLM NameMistral Ei Oc Unstructured Train
Repository 🤗https://huggingface.co/Holmeister/Mistral_ei_oc_unstructured_train 
Base Model(s)  mistralai/Mistral-7B-v0.3   mistralai/Mistral-7B-v0.3
Model Size7b
Required VRAM0.1 GB
Updated2024-11-27
MaintainerHolmeister
Model Files  0.1 GB   0.0 GB
Model ArchitectureAdapter
Is Biasednone
Tokenizer ClassLlamaTokenizer
Padding Token</s>
PEFT TypeLORA
LoRA ModelYes
PEFT Target Modulesq_proj|gate_proj|up_proj|o_proj|v_proj|k_proj|down_proj
LoRA Alpha16
LoRA Dropout0.1
R Param8

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Note: green Score (e.g. "73.2") means that the model is better than Holmeister/Mistral_ei_oc_unstructured_train.

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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227
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