anamikac2708
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Update README.md
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README.md
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@@ -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)
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@@ -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,
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