HuggingFaceH4/ultrachat_200k
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How to use QinLiuNLP/llama3-sudo-sanity with PEFT:
from peft import PeftModel
from transformers import AutoModelForCausalLM
base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Meta-Llama-3-8B")
model = PeftModel.from_pretrained(base_model, "QinLiuNLP/llama3-sudo-sanity")This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B on the HuggingFaceH4/ultrachat_200k dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.8735 | 0.9899 | 49 | 1.8325 |
| 1.8231 | 2.0 | 99 | 1.7239 |
| 1.7516 | 2.9899 | 148 | 1.6330 |
| 1.6586 | 4.0 | 198 | 1.5280 |
| 1.5571 | 4.9899 | 247 | 1.4166 |
| 1.4677 | 6.0 | 297 | 1.3068 |
| 1.3422 | 6.9899 | 346 | 1.2082 |
| 1.2609 | 8.0 | 396 | 1.1378 |
| 1.1647 | 8.9899 | 445 | 1.1074 |
| 1.1571 | 9.8990 | 490 | 1.1030 |
Base model
meta-llama/Meta-Llama-3-8B