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metadata
tags:
  - trl
  - dpo
  - generated_from_trainer
model-index:
  - name: arceeai-cpt-sft-dpo-full
    results: []

arceeai-cpt-sft-dpo-full

This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4290
  • Rewards/chosen: -2.1400
  • Rewards/rejected: -3.3730
  • Rewards/accuracies: 0.7680
  • Rewards/margins: 1.2330
  • Logps/rejected: -667.6970
  • Logps/chosen: -599.8088
  • Logits/rejected: -3.8772
  • Logits/chosen: -3.7995

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: 4
  • eval_batch_size: 2
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • 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 Logps/rejected Logps/chosen Logits/rejected Logits/chosen
0.6051 0.1 100 0.5848 -0.2214 -0.5948 0.6920 0.3733 -389.8707 -407.9477 -3.9800 -3.8777
0.5134 0.21 200 0.5025 -1.5935 -2.5024 0.7160 0.9089 -580.6380 -545.1561 -3.9154 -3.8176
0.4489 0.31 300 0.4614 -1.5620 -2.6097 0.7760 1.0477 -591.3610 -542.0072 -3.7594 -3.6703
0.4359 0.42 400 0.4467 -2.0879 -3.2160 0.7680 1.1281 -651.9947 -594.5918 -3.7022 -3.6221
0.4271 0.52 500 0.4441 -2.0549 -3.2181 0.7840 1.1631 -652.2027 -591.3006 -3.8189 -3.7408
0.4181 0.63 600 0.4366 -1.9876 -3.1678 0.7760 1.1802 -647.1777 -584.5698 -3.7950 -3.7170
0.4 0.73 700 0.4317 -2.1647 -3.3521 0.7640 1.1874 -665.6046 -602.2762 -3.8739 -3.7970
0.4123 0.84 800 0.4291 -2.2039 -3.4491 0.7680 1.2453 -675.3075 -606.1934 -3.8606 -3.7827
0.4394 0.94 900 0.4292 -2.1325 -3.3633 0.7680 1.2308 -666.7250 -599.0574 -3.8777 -3.8001

Framework versions

  • Transformers 4.36.2
  • Pytorch 2.1.2+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.0