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20240818_gemma-2-2b-it_full-anonymous-617_dpo-sft_BFI

This model is a fine-tuned version of google/gemma-2-2b-it on the BFI-anonymous-617_dpo_no-system_sharegpt_105 dataset. It achieves the following results on the evaluation set:

  • Loss: 1.8025
  • Rewards/chosen: 8.8006
  • Rewards/rejected: 3.5406
  • Rewards/accuracies: 0.9247
  • Rewards/margins: 5.2600
  • Logps/rejected: -78.8782
  • Logps/chosen: -118.9999
  • Logits/rejected: -4.3666
  • Logits/chosen: -4.5476

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: 1
  • eval_batch_size: 1
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 4
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 32
  • total_eval_batch_size: 4
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 3.0

Training results

Training Loss Epoch Step Validation Loss Rewards/chosen Rewards/rejected Rewards/accuracies Rewards/margins Logps/rejected Logps/chosen Logits/rejected Logits/chosen
2.1444 0.4365 500 2.1669 6.0677 3.1466 0.9032 2.9211 -82.8180 -146.3293 0.2298 0.0904
1.9865 0.8731 1000 2.0409 6.5585 2.8550 0.8710 3.7036 -85.7341 -141.4206 1.2474 1.0619
1.4582 1.3096 1500 1.8728 8.1097 3.6131 0.9247 4.4967 -78.1532 -125.9085 -0.5647 -0.7531
1.4326 1.7462 2000 1.7866 8.5668 3.5837 0.9247 4.9831 -78.4469 -121.3381 -1.9024 -2.0860
1.0857 2.1827 2500 1.8025 8.6210 3.5507 0.9247 5.0704 -78.7771 -120.7956 -3.4905 -3.6840
1.0376 2.6192 3000 1.8047 8.7683 3.5103 0.9247 5.2580 -79.1805 -119.3225 -4.2916 -4.4732

Framework versions

  • Transformers 4.43.1
  • Pytorch 2.3.0a0+ebedce2
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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