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vanilla_dpo_iter_4

This model is a fine-tuned version of YYYYYYibo/vanilla_dpo_iter_3 on the updated and the original datasets. It achieves the following results on the evaluation set:

  • Loss: 0.5941
  • Rewards/chosen: -0.4399
  • Rewards/rejected: -0.7506
  • Rewards/accuracies: 0.7020
  • Rewards/margins: 0.3107
  • Logps/rejected: -356.7067
  • Logps/chosen: -337.8192
  • Logits/rejected: -2.0692
  • Logits/chosen: -2.2237

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: 5e-06
  • train_batch_size: 2
  • eval_batch_size: 2
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 4
  • gradient_accumulation_steps: 16
  • total_train_batch_size: 128
  • total_eval_batch_size: 8
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss Rewards/chosen Rewards/rejected Rewards/accuracies Rewards/margins Logps/rejected Logps/chosen Logits/rejected Logits/chosen
0.5962 0.64 100 0.5941 -0.4399 -0.7506 0.7020 0.3107 -356.7067 -337.8192 -2.0692 -2.2237

Framework versions

  • PEFT 0.7.1
  • Transformers 4.36.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.14.6
  • Tokenizers 0.15.2
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