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  ---
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  license: unlicense
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  ---
 
 
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  This is a testing LORA for Llama-3 8B or Llama-3 8B Instruct. The goal for this model was to bring back some of the expressive prose and writing style of the base model, as well as shift the rather dry style of the 8B instruct.
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- Data Processing
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- Raw Data to Custom Data
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- Started with ~40GB of raw data
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- Aggressively selected for writing style
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- Cleaned multiple times both automatically and by hand
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- Final dataset size: 78.4MB
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- No synthetic data present in the used dataset
 
 
 
 
 
 
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- Data Cleaning Code
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  Once the training is verified to be beneficial (and thus the cleaning was likely to be correct), the data cleaning code will be released.
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- Training Procedure
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- Training Framework
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- Training was done QLORA style via Axolotl. The full training script along with the data processing scripts will be released similarly once the procedure is verified to benefit the model in a useful way.
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- Training Parameters
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-
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- Base Model: Llama 3 8B (Non instruct)
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- r: 4
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- alpha: 8
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- dropout: 0
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- warmup: 45 steps
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- epochs: 2
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- lr: constant with warmup
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- optimizer: adamw (torch fused)
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- weight decay: 0.1
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- adam_b1: 0.9
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- adam_b2: 0.999
 
 
 
 
 
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  ---
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  license: unlicense
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  ---
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+ ## Overview
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+
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  This is a testing LORA for Llama-3 8B or Llama-3 8B Instruct. The goal for this model was to bring back some of the expressive prose and writing style of the base model, as well as shift the rather dry style of the 8B instruct.
 
 
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+ ## Data Processing
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+
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+ ### Raw Data to Custom Data
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+
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+ - Started with ~40GB of raw data
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+ - Aggressively selected for writing style
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+ - Cleaned multiple times both automatically and by hand
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+ - Final dataset size: 78.4MB
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+ - No synthetic data present in the used dataset
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+
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+ ### Data Cleaning Code
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  Once the training is verified to be beneficial (and thus the cleaning was likely to be correct), the data cleaning code will be released.
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+
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+ ## Training Procedure
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+
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+ ### Training Framework
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+
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+ Training was done QLORA style via [Axolotl](https://github.com/OpenAccess-AI-Collective/axolotl). The full training script along with the data processing scripts will be released similarly once the procedure is verified to benefit the model in a useful way.
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+
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+ ### Training Parameters
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+
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+ - Base Model: Llama 3 8B (Non instruct)
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+ - r: 4
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+ - alpha: 8
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+ - dropout: 0
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+ - warmup: 45 steps
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+ - epochs: 2
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+ - lr: constant with warmup
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+ - optimizer: adamw (torch fused)
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+ - weight decay: 0.1
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+ - adam_b1: 0.9
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+ - adam_b2: 0.999