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Update README.md

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@@ -12,7 +12,7 @@ This repository contains the LORA weights finetuned on the translated version of
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  ## Training procedure
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- The training was done on the 7B LLaMA model (decapoda-research/llama-7b-hf) quantized to 8bits with following Hyperparameters:
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  ```
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  MICRO_BATCH_SIZE = 3
@@ -20,13 +20,13 @@ BATCH_SIZE = 128
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  GRADIENT_ACCUMULATION_STEPS = BATCH_SIZE // MICRO_BATCH_SIZE
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  EPOCHS = 2 # paper uses 3
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  LEARNING_RATE = 2e-5 # from the original paper
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- CUTOFF_LEN = 256 # 256 accounts for about 96% of the data
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  LORA_R = 4
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  LORA_ALPHA = 16
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  LORA_DROPOUT = 0.05
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  ```
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- The sole goal of this project is to explore the effects of single language finetuning using the same dataset and methods as the original paper did and comapre the results
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  @misc{alpaca,
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  author = {Rohan Taori and Ishaan Gulrajani and Tianyi Zhang and Yann Dubois and Xuechen Li and Carlos Guestrin and Percy Liang and Tatsunori B. Hashimoto },
 
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  ## Training procedure
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+ The training was done on the 7B LLaMA model (decapoda-research/llama-7b-hf) quantized to 8bits with the following Hyperparameters:
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  ```
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  MICRO_BATCH_SIZE = 3
 
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  GRADIENT_ACCUMULATION_STEPS = BATCH_SIZE // MICRO_BATCH_SIZE
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  EPOCHS = 2 # paper uses 3
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  LEARNING_RATE = 2e-5 # from the original paper
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+ CUTOFF_LEN = 256
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  LORA_R = 4
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  LORA_ALPHA = 16
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  LORA_DROPOUT = 0.05
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  ```
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+ The sole goal of this project is to explore the effects of single-language finetuning using the same dataset and methods as the original paper did and comapre the results
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  @misc{alpaca,
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  author = {Rohan Taori and Ishaan Gulrajani and Tianyi Zhang and Yann Dubois and Xuechen Li and Carlos Guestrin and Percy Liang and Tatsunori B. Hashimoto },