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zephyr-7b-dpo-full-gpt-low-curriculum

This model is a fine-tuned version of alignment-handbook/zephyr-7b-sft-full on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5229
  • Rewards/chosen: -0.8152
  • Rewards/rejected: -1.5392
  • Rewards/accuracies: 0.7069
  • Rewards/margins: 0.7241
  • Logps/rejected: -399.5724
  • Logps/chosen: -365.5233
  • Logits/rejected: 1.4072
  • Logits/chosen: 0.3892

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: 8
  • eval_batch_size: 8
  • seed: 55
  • distributed_type: multi-GPU
  • num_devices: 8
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 128
  • total_eval_batch_size: 64
  • 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
0.6558 0.1147 50 0.6455 0.0044 -0.0965 0.6810 0.1009 -255.3015 -283.5690 -2.4863 -2.5882
0.5907 0.2294 100 0.5894 -0.2321 -0.5376 0.7069 0.3055 -299.4117 -307.2200 -2.4655 -2.5910
0.5657 0.3440 150 0.5474 -0.5168 -1.0293 0.7198 0.5125 -348.5750 -335.6879 -0.6546 -1.0350
0.5303 0.4587 200 0.5414 -1.0659 -1.7181 0.75 0.6522 -417.4532 -390.5937 0.7246 0.0707
0.5472 0.5734 250 0.5268 -0.8095 -1.4718 0.7155 0.6623 -392.8294 -364.9606 1.2657 0.4213
0.5517 0.6881 300 0.5284 -0.8914 -1.6145 0.7112 0.7231 -407.0940 -373.1438 1.3137 0.2994
0.4943 0.8028 350 0.5237 -0.8328 -1.5668 0.7112 0.7339 -402.3227 -367.2895 1.4252 0.4044
0.5335 0.9174 400 0.5229 -0.8152 -1.5392 0.7069 0.7241 -399.5724 -365.5233 1.4072 0.3892

Framework versions

  • Transformers 4.44.0.dev0
  • Pytorch 2.1.2
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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