llama-duo/synth_summarize_dataset_dedup
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How to use llama-duo/gemma7b-summarize-gemini1_5flash-64k with PEFT:
from peft import PeftModel
from transformers import AutoModelForCausalLM
base_model = AutoModelForCausalLM.from_pretrained("google/gemma-7b")
model = PeftModel.from_pretrained(base_model, "llama-duo/gemma7b-summarize-gemini1_5flash-64k")This model is a fine-tuned version of google/gemma-7b on the llama-duo/synth_summarize_dataset_dedup 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 |
|---|---|---|---|
| 1.2495 | 0.9952 | 104 | 2.6543 |
| 1.0258 | 2.0 | 209 | 2.5232 |
| 0.9351 | 2.9952 | 313 | 2.4668 |
| 0.8914 | 4.0 | 418 | 2.4789 |
| 0.8487 | 4.9952 | 522 | 2.4752 |
| 0.8222 | 6.0 | 627 | 2.4928 |
| 0.7746 | 6.9952 | 731 | 2.4925 |
| 0.7644 | 8.0 | 836 | 2.5051 |
| 0.7578 | 8.9952 | 940 | 2.5211 |
| 0.7589 | 9.9522 | 1040 | 2.5156 |
Base model
google/gemma-7b