# LLaMa-7B LoRA Alpaca-25
This repo contains a low-rank adaptation (LoRA) finetuned model of LLaMa-7B on 25% of the Alpaca cleaned dataset.
This version of the weights was trained with the following hyperparameters:
* Epochs: 3
* Cutoff length: 512
* Learning rate: 3e-4
* Lora r: 8
* Lora alpha: 16
* Lora dropout: 0.05
* Lora target modules: q_proj, k_proj
{"license": "mit", "datasets": ["magicgh/alpaca-cleaned-random-25"]}
dataset:magicgh/alpaca-cleaned-random-25 license:mit region:us
TAGS
#dataset-magicgh/alpaca-cleaned-random-25 #license-mit #region-us 

# LLaMa-7B LoRA Alpaca-25
This repo contains a low-rank adaptation (LoRA) finetuned model of LLaMa-7B on 25% of the Alpaca cleaned dataset.
This version of the weights was trained with the following hyperparameters:
* Epochs: 3
* Cutoff length: 512
* Learning rate: 3e-4
* Lora r: 8
* Lora alpha: 16
* Lora dropout: 0.05
* Lora target modules: q_proj, k_proj
# LLaMa-7B LoRA Alpaca-25
This repo contains a low-rank adaptation (LoRA) finetuned model of LLaMa-7B on 25% of the Alpaca cleaned dataset.
This version of the weights was trained with the following hyperparameters:
* Epochs: 3
* Cutoff length: 512
* Learning rate: 3e-4
* Lora r: 8
* Lora alpha: 16
* Lora dropout: 0.05
* Lora target modules: q_proj, k_proj
TAGS
#dataset-magicgh/alpaca-cleaned-random-25 #license-mit #region-us 
 # LLaMa-7B LoRA Alpaca-25
This repo contains a low-rank adaptation (LoRA) finetuned model of LLaMa-7B on 25% of the Alpaca cleaned dataset.
This version of the weights was trained with the following hyperparameters:
* Epochs: 3
* Cutoff length: 512
* Learning rate: 3e-4
* Lora r: 8
* Lora alpha: 16
* Lora dropout: 0.05
* Lora target modules: q_proj, k_proj
TAGS
#dataset-magicgh/alpaca-cleaned-random-25 #license-mit #region-us 
# LLaMa-7B LoRA Alpaca-25
This repo contains a low-rank adaptation (LoRA) finetuned model of LLaMa-7B on 25% of the Alpaca cleaned dataset.
This version of the weights was trained with the following hyperparameters:
* Epochs: 3
* Cutoff length: 512
* Learning rate: 3e-4
* Lora r: 8
* Lora alpha: 16
* Lora dropout: 0.05
* Lora target modules: q_proj, k_proj