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model_shp4_dpo1

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:

  • Loss: 1.7562
  • Rewards/chosen: -8.5308
  • Rewards/rejected: -8.4695
  • Rewards/accuracies: 0.5200
  • Rewards/margins: -0.0613
  • Logps/rejected: -331.4397
  • Logps/chosen: -314.9189
  • Logits/rejected: -1.1613
  • Logits/chosen: -1.1692

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.0005
  • train_batch_size: 4
  • eval_batch_size: 1
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 100
  • training_steps: 1000

Training results

Training Loss Epoch Step Validation Loss Rewards/chosen Rewards/rejected Rewards/accuracies Rewards/margins Logps/rejected Logps/chosen Logits/rejected Logits/chosen
0.0922 2.67 100 1.1410 -4.1724 -4.0602 0.5600 -0.1122 -287.3470 -271.3348 -0.9400 -0.9462
0.0014 5.33 200 1.6279 -8.0256 -7.9377 0.5400 -0.0879 -326.1222 -309.8669 -1.2061 -1.2156
0.0001 8.0 300 1.6781 -7.8271 -7.7492 0.4900 -0.0780 -324.2366 -307.8824 -1.1931 -1.2019
0.0001 10.67 400 1.7244 -8.2046 -8.1268 0.5100 -0.0778 -328.0134 -311.6574 -1.1773 -1.1864
0.0001 13.33 500 1.7449 -8.3826 -8.3126 0.5100 -0.0701 -329.8707 -313.4376 -1.1689 -1.1774
0.0001 16.0 600 1.7522 -8.4707 -8.4001 0.5100 -0.0706 -330.7461 -314.3180 -1.1649 -1.1729
0.0001 18.67 700 1.7553 -8.5177 -8.4517 0.5200 -0.0659 -331.2625 -314.7882 -1.1626 -1.1704
0.0001 21.33 800 1.7608 -8.5360 -8.4723 0.5200 -0.0637 -331.4679 -314.9713 -1.1608 -1.1692
0.0001 24.0 900 1.7653 -8.5361 -8.4664 0.5200 -0.0697 -331.4087 -314.9720 -1.1617 -1.1693
0.0001 26.67 1000 1.7562 -8.5308 -8.4695 0.5200 -0.0613 -331.4397 -314.9189 -1.1613 -1.1692

Framework versions

  • PEFT 0.10.0
  • Transformers 4.39.1
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2
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