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stablelm-2-1_6b-orpo-full-v1

This model is a fine-tuned version of stabilityai/stablelm-2-1_6b on the alvarobartt/dpo-mix-7k-simplified dataset. It achieves the following results on the evaluation set:

  • Loss: 1.3790
  • Rewards/chosen: -0.1279
  • Rewards/rejected: -0.1387
  • Rewards/accuracies: 0.5625
  • Rewards/margins: 0.0114
  • Logps/rejected: -1.3906
  • Logps/chosen: -1.2734
  • Logits/rejected: -2.4688
  • Logits/chosen: -2.4844
  • Nll Loss: 1.3359
  • Log Odds Ratio: -0.6799
  • Log Odds Chosen: 0.1751

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: 42
  • distributed_type: multi-GPU
  • num_devices: 3
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 48
  • total_eval_batch_size: 24
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 2

Training results

Training Loss Epoch Step Validation Loss Rewards/chosen Rewards/rejected Rewards/accuracies Rewards/margins Logps/rejected Logps/chosen Logits/rejected Logits/chosen Nll Loss Log Odds Ratio Log Odds Chosen
1.4572 0.71 100 1.4374 -0.1406 -0.1514 0.5469 0.0109 -1.5078 -1.4062 -2.3594 -2.375 1.3906 -0.6874 0.1528
1.3846 1.42 200 1.3829 -0.1279 -0.1396 0.5625 0.0115 -1.3984 -1.2812 -2.4688 -2.4844 1.3359 -0.6793 0.1746

Framework versions

  • Transformers 4.39.0.dev0
  • Pytorch 2.2.1
  • Datasets 2.18.0
  • Tokenizers 0.15.2
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Dataset used to train vain05/stablelm-2-1_6b-orpo-full-v1