llama-duo/synth_summarize_dataset_dedup
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How to use llama-duo/gemma2b-summarize-gemini1_5flash-32k with PEFT:
from peft import PeftModel
from transformers import AutoModelForCausalLM
base_model = AutoModelForCausalLM.from_pretrained("google/gemma-2b")
model = PeftModel.from_pretrained(base_model, "llama-duo/gemma2b-summarize-gemini1_5flash-32k")This model is a fine-tuned version of google/gemma-2b 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 |
|---|---|---|---|
| 2.0459 | 1.0 | 26 | 2.8633 |
| 1.2724 | 2.0 | 52 | 2.7063 |
| 1.1654 | 3.0 | 78 | 2.6695 |
| 1.1056 | 4.0 | 104 | 2.6545 |
| 1.0615 | 5.0 | 130 | 2.6669 |
| 1.0347 | 6.0 | 156 | 2.6682 |
| 1.0216 | 7.0 | 182 | 2.6747 |
| 1.0204 | 8.0 | 208 | 2.6796 |
| 1.0071 | 9.0 | 234 | 2.6812 |
| 1.0088 | 10.0 | 260 | 2.6817 |
Base model
google/gemma-2b