llama-duo/synth_summarize_dataset_dedup
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How to use llama-duo/gemma2b-summarize-gemini1_5flash-16k 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-16k")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 |
|---|---|---|---|
| 2.0246 | 0.9811 | 26 | 2.6613 |
| 1.3202 | 2.0 | 53 | 2.5405 |
| 1.1694 | 2.9811 | 79 | 2.5125 |
| 1.1076 | 4.0 | 106 | 2.5138 |
| 1.0651 | 4.9811 | 132 | 2.5086 |
| 1.0394 | 6.0 | 159 | 2.5248 |
| 1.0232 | 6.9811 | 185 | 2.5264 |
| 1.0042 | 8.0 | 212 | 2.5296 |
| 1.0109 | 8.9811 | 238 | 2.5319 |
| 1.0064 | 9.8113 | 260 | 2.5319 |
Base model
google/gemma-2b