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Update README.md

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  1. README.md +4 -2
README.md CHANGED
@@ -9,6 +9,7 @@ tags:
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  - llama
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  - trl
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  - finlang
 
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  base_model: unsloth/llama-3-8b-bnb-4bit
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  ---
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@@ -34,7 +35,8 @@ max_seq_length=2048
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  model, tokenizer = FastLanguageModel.from_pretrained(
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  model_name = "anamikac2708/Llama3-8b-finetuned-investopedia-Merged-FP16", # YOUR MODEL YOU USED FOR TRAINING
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  max_seq_length = max_seq_length,
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- dtype = torch.bfloat16
 
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  )
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  tokenizer = AutoTokenizer.from_pretrained(model_id)
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  pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
@@ -77,7 +79,7 @@ Hyperparameters:
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  }
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  ```
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- Model was trained on 1xA100 80GB, below loss and memory consmuption details:
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  {'eval_loss': 0.9614351987838745,
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  'eval_runtime': 244.0411,
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  'eval_samples_per_second': 2.663,
 
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  - llama
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  - trl
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  - finlang
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+ - qlora
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  base_model: unsloth/llama-3-8b-bnb-4bit
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  ---
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  model, tokenizer = FastLanguageModel.from_pretrained(
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  model_name = "anamikac2708/Llama3-8b-finetuned-investopedia-Merged-FP16", # YOUR MODEL YOU USED FOR TRAINING
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  max_seq_length = max_seq_length,
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+ dtype = torch.bfloat16,
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+ #load_in_4bit = True, # IF YOU WANT TO LOAD WITH BITSANDBYTES INT4
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  )
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  tokenizer = AutoTokenizer.from_pretrained(model_id)
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  pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
 
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  }
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  ```
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+ ## Model was trained on 1xA100 80GB, below loss and memory consmuption details:
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  {'eval_loss': 0.9614351987838745,
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  'eval_runtime': 244.0411,
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  'eval_samples_per_second': 2.663,