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tulu2-13b-cost-tulumix-5e-7-nojudge

This model is a fine-tuned version of allenai/tulu-2-13b on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6915
  • Rewards/chosen: 0.0201
  • Rewards/rejected: 0.0161
  • Rewards/accuracies: 0.5510
  • Rewards/margins: 0.0040
  • Rewards/margins Max: 0.0645
  • Rewards/margins Min: -0.0595
  • Rewards/margins Std: 0.0411
  • Logps/rejected: -314.0515
  • Logps/chosen: -322.9527
  • Logits/rejected: -0.8949
  • Logits/chosen: -1.0172

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: 8
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 2
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 8
  • total_eval_batch_size: 16
  • 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 Rewards/margins Max Rewards/margins Min Rewards/margins Std Logps/rejected Logps/chosen Logits/rejected Logits/chosen
0.6659 1.0 4424 0.6915 0.0201 0.0161 0.5510 0.0040 0.0645 -0.0595 0.0411 -314.0515 -322.9527 -0.8949 -1.0172

Framework versions

  • PEFT 0.7.1
  • Transformers 4.39.0.dev0
  • Pytorch 2.1.2+cu121
  • Datasets 2.14.6
  • Tokenizers 0.15.2
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