28 lines
988 B
Markdown
28 lines
988 B
Markdown
---
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datasets:
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- heegyu/wizard_vicuna_70k_v2
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license: apache-2.0
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---
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Hyperparameters
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- 3/8 epoch(3rd epoch checkpoing while 8epoch training)
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- 1e-4 -> 1e-5 with cosine lr decay
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- batch size 128
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- max sequence length 2048
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- AdamW(weigth decay=0.01, b1=0.9, b2=0.99, grad_clip=1.0)
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- no warmup
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- BF16
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- Base Model: [openlm-research/open_llama_3b_v2](https://huggingface.co/openlm-research/open_llama_3b_v2)
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```
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from transformers import AutoTokenizer, AutoModelForCausalLM
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tokenizer = AutoTokenizer.from_pretrained("heegyu/WizardVicuna-open-llama-3b-v2")
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model = AutoModelForCausalLM.from_pretrained("heegyu/WizardVicuna-open-llama-3b-v2")
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inputs = tokenizer(["Human: Hi, nice to meet you!\n\nAssistant: "], return_tensors="pt")
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outputs = model.generate(**inputs, max_new_tokens=16)
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print(tokenizer.batch_decode(outputs, skip_special_tokens=False))
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```
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output: `['Human: Hi, nice to meet you!\n\nAssistant: Hello. Great to meet you too. Well, how can I assist you today?<|endoftext|>']` |