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guoyu-zhang/model_shp1_dpo1
model_shp1_dpo1 is a machine learning model from guoyu-zhang. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as llama2.
should probably proofread and complete it, then remove this comment. --
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From the Hugging Face model README
This model is a fine-tuned version of meta-llama/Llama-2-7b-chat-hf on an unknown dataset. It achieves the following results on the evaluation set:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.0741 | 2.67 | 100 | 1.1825 | -3.1899 | -3.0393 | 0.4800 | -0.1506 | -244.8796 | -279.3668 | -1.2034 | -1.2620 |
| 0.0016 | 5.33 | 200 | 2.1179 | -8.9597 | -8.2224 | 0.4100 | -0.7372 | -296.7111 | -337.0645 | -1.1154 | -1.1503 |
| 0.0001 | 8.0 | 300 | 1.9624 | -9.5308 | -9.0562 | 0.4500 | -0.4746 | -305.0487 | -342.7763 | -1.0878 | -1.1168 |
| 0.0001 | 10.67 | 400 | 1.9799 | -9.6041 | -9.1296 | 0.4500 | -0.4745 | -305.7831 | -343.5089 | -1.0797 | -1.1079 |
| 0.0001 | 13.33 | 500 | 1.9938 | -9.6787 | -9.2063 | 0.4500 | -0.4724 | -306.5495 | -344.2545 | -1.0746 | -1.1031 |
| 0.0001 | 16.0 | 600 | 2.0046 | -9.7222 | -9.2446 | 0.4600 | -0.4776 | -306.9330 | -344.6898 | -1.0722 | -1.0999 |
| 0.0001 | 18.67 | 700 | 2.0079 | -9.7525 | -9.2749 | 0.4500 | -0.4776 | -307.2361 | -344.9933 | -1.0706 | -1.0984 |
| 0.0001 | 21.33 | 800 | 2.0091 | -9.7588 | -9.2867 | 0.4600 | -0.4721 | -307.3541 | -345.0561 | -1.0699 | -1.0978 |
| 0.0001 | 24.0 | 900 | 2.0158 | -9.7704 | -9.2915 | 0.4500 | -0.4789 | -307.4015 | -345.1719 | -1.0694 | -1.0975 |
| 0.0001 | 26.67 | 1000 | 2.0112 | -9.7625 | -9.2926 | 0.4700 | -0.4699 | -307.4124 | -345.0927 | -1.0692 | -1.0975 |