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falcon-7b-dpo-lora

This model is a fine-tuned version of tiiuae/falcon-7b on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6909
  • Rewards/chosen: 0.0159
  • Rewards/rejected: 0.0096
  • Rewards/accuracies: 0.3175
  • Rewards/margins: 0.0063
  • Logps/rejected: -88.4353
  • Logps/chosen: -109.9771
  • Logits/rejected: -14.9384
  • Logits/chosen: -14.8499

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-07
  • train_batch_size: 2
  • eval_batch_size: 4
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • gradient_accumulation_steps: 32
  • total_train_batch_size: 512
  • total_eval_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss Rewards/chosen Rewards/rejected Rewards/accuracies Rewards/margins Logps/rejected Logps/chosen Logits/rejected Logits/chosen
0.6927 1.0 121 0.6929 0.0035 0.0015 0.2857 0.0020 -88.5168 -110.1007 -14.9346 -14.8473
0.6915 2.0 242 0.6917 0.0116 0.0071 0.3056 0.0045 -88.4605 -110.0199 -14.9351 -14.8469
0.6913 3.0 363 0.6909 0.0159 0.0096 0.3175 0.0063 -88.4353 -109.9771 -14.9384 -14.8499

Framework versions

  • Transformers 4.35.0
  • Pytorch 2.1.2+cu121
  • Datasets 2.14.6
  • Tokenizers 0.14.1
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