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deepseek-8b-orpo-lora

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metadata
base_model: deepseek-ai/deepseek-math-7b-base
datasets:
  - zfz1/my_preference_gsm8k_deepseek
library_name: peft
license: other
tags:
  - alignment-handbook
  - trl
  - orpo
  - generated_from_trainer
model-index:
  - name: deepseek-8b-orpo-lora
    results: []

Visualize in Weights & Biases

deepseek-8b-orpo-lora

This model is a fine-tuned version of deepseek-ai/deepseek-math-7b-base on the zfz1/my_preference_gsm8k_deepseek dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6818
  • Rewards/chosen: -0.0338
  • Rewards/rejected: -0.0840
  • Rewards/accuracies: 0.8088
  • Rewards/margins: 0.0502
  • Logps/rejected: -0.8398
  • Logps/chosen: -0.3377
  • Logits/rejected: 34.4233
  • Logits/chosen: 35.5254
  • Nll Loss: 0.6414
  • Log Odds Ratio: -0.4212
  • Log Odds Chosen: 1.0634

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: 0.0001
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 43
  • distributed_type: multi-GPU
  • num_devices: 4
  • 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: 2

Training results

Framework versions

  • PEFT 0.11.1
  • Transformers 4.42.3
  • Pytorch 2.1.2
  • Datasets 2.20.0
  • Tokenizers 0.19.1