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tsavage68
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UTI2_L3_1000steps_1e5rate_05beta_CSFTDPO

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dpo
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UTI2_L3_1000steps_1e5rate_05beta_CSFTDPO / README.md
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metadata
license: llama3
base_model: tsavage68/UTI_L3_1000steps_1e5rate_SFT
tags:
  - trl
  - dpo
  - generated_from_trainer
model-index:
  - name: UTI2_L3_1000steps_1e5rate_05beta_CSFTDPO
    results: []

UTI2_L3_1000steps_1e5rate_05beta_CSFTDPO

This model is a fine-tuned version of tsavage68/UTI_L3_1000steps_1e5rate_SFT on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6931
  • Rewards/chosen: 0.0
  • Rewards/rejected: 0.0
  • Rewards/accuracies: 0.0
  • Rewards/margins: 0.0
  • Logps/rejected: 0.0
  • Logps/chosen: 0.0
  • Logits/rejected: -1.1794
  • Logits/chosen: -1.1794

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: 1e-05
  • train_batch_size: 2
  • eval_batch_size: 1
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 4
  • 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
0.6931 0.3333 25 0.6931 0.0 0.0 0.0 0.0 0.0 0.0 -1.1794 -1.1794
0.6931 0.6667 50 0.6931 0.0 0.0 0.0 0.0 0.0 0.0 -1.1794 -1.1794
0.6931 1.0 75 0.6931 0.0 0.0 0.0 0.0 0.0 0.0 -1.1794 -1.1794
0.6931 1.3333 100 0.6931 0.0 0.0 0.0 0.0 0.0 0.0 -1.1794 -1.1794
0.6931 1.6667 125 0.6931 0.0 0.0 0.0 0.0 0.0 0.0 -1.1794 -1.1794
0.6931 2.0 150 0.6931 0.0 0.0 0.0 0.0 0.0 0.0 -1.1794 -1.1794
0.6931 2.3333 175 0.6931 0.0 0.0 0.0 0.0 0.0 0.0 -1.1794 -1.1794
0.6931 2.6667 200 0.6931 0.0 0.0 0.0 0.0 0.0 0.0 -1.1794 -1.1794
0.6931 3.0 225 0.6931 0.0 0.0 0.0 0.0 0.0 0.0 -1.1794 -1.1794
0.6931 3.3333 250 0.6931 0.0 0.0 0.0 0.0 0.0 0.0 -1.1794 -1.1794
0.6931 3.6667 275 0.6931 0.0 0.0 0.0 0.0 0.0 0.0 -1.1794 -1.1794
0.6931 4.0 300 0.6931 0.0 0.0 0.0 0.0 0.0 0.0 -1.1794 -1.1794
0.6931 4.3333 325 0.6931 0.0 0.0 0.0 0.0 0.0 0.0 -1.1794 -1.1794
0.6931 4.6667 350 0.6931 0.0 0.0 0.0 0.0 0.0 0.0 -1.1794 -1.1794
0.6931 5.0 375 0.6931 0.0 0.0 0.0 0.0 0.0 0.0 -1.1794 -1.1794
0.6931 5.3333 400 0.6931 0.0 0.0 0.0 0.0 0.0 0.0 -1.1794 -1.1794
0.6931 5.6667 425 0.6931 0.0 0.0 0.0 0.0 0.0 0.0 -1.1794 -1.1794
0.6931 6.0 450 0.6931 0.0 0.0 0.0 0.0 0.0 0.0 -1.1794 -1.1794
0.6931 6.3333 475 0.6931 0.0 0.0 0.0 0.0 0.0 0.0 -1.1794 -1.1794
0.6931 6.6667 500 0.6931 0.0 0.0 0.0 0.0 0.0 0.0 -1.1794 -1.1794
0.6931 7.0 525 0.6931 0.0 0.0 0.0 0.0 0.0 0.0 -1.1794 -1.1794
0.6931 7.3333 550 0.6931 0.0 0.0 0.0 0.0 0.0 0.0 -1.1794 -1.1794
0.6931 7.6667 575 0.6931 0.0 0.0 0.0 0.0 0.0 0.0 -1.1794 -1.1794
0.6931 8.0 600 0.6931 0.0 0.0 0.0 0.0 0.0 0.0 -1.1794 -1.1794
0.6931 8.3333 625 0.6931 0.0 0.0 0.0 0.0 0.0 0.0 -1.1794 -1.1794
0.6931 8.6667 650 0.6931 0.0 0.0 0.0 0.0 0.0 0.0 -1.1794 -1.1794
0.6931 9.0 675 0.6931 0.0 0.0 0.0 0.0 0.0 0.0 -1.1794 -1.1794
0.6931 9.3333 700 0.6931 0.0 0.0 0.0 0.0 0.0 0.0 -1.1794 -1.1794
0.6931 9.6667 725 0.6931 0.0 0.0 0.0 0.0 0.0 0.0 -1.1794 -1.1794
0.6931 10.0 750 0.6931 0.0 0.0 0.0 0.0 0.0 0.0 -1.1794 -1.1794
0.6931 10.3333 775 0.6931 0.0 0.0 0.0 0.0 0.0 0.0 -1.1794 -1.1794
0.6931 10.6667 800 0.6931 0.0 0.0 0.0 0.0 0.0 0.0 -1.1794 -1.1794
0.6931 11.0 825 0.6931 0.0 0.0 0.0 0.0 0.0 0.0 -1.1794 -1.1794
0.6931 11.3333 850 0.6931 0.0 0.0 0.0 0.0 0.0 0.0 -1.1794 -1.1794
0.6931 11.6667 875 0.6931 0.0 0.0 0.0 0.0 0.0 0.0 -1.1794 -1.1794
0.6931 12.0 900 0.6931 0.0 0.0 0.0 0.0 0.0 0.0 -1.1794 -1.1794
0.6931 12.3333 925 0.6931 0.0 0.0 0.0 0.0 0.0 0.0 -1.1794 -1.1794
0.6931 12.6667 950 0.6931 0.0 0.0 0.0 0.0 0.0 0.0 -1.1794 -1.1794
0.6931 13.0 975 0.6931 0.0 0.0 0.0 0.0 0.0 0.0 -1.1794 -1.1794
0.6931 13.3333 1000 0.6931 0.0 0.0 0.0 0.0 0.0 0.0 -1.1794 -1.1794

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.0.0+cu117
  • Datasets 2.19.2
  • Tokenizers 0.19.1