zephyr-7b-dpo-lora / README.md
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metadata
base_model: mistralai/Mistral-7B-v0.1
library_name: peft
license: apache-2.0
tags:
  - alignment-handbook
  - trl
  - dpo
  - generated_from_trainer
model-index:
  - name: zephyr-7b-dpo-lora
    results: []

zephyr-7b-dpo-lora

This model is a fine-tuned version of alignment-handbook/zephyr-7b-sft-qlora on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4930
  • Rewards/chosen: -1.7956
  • Rewards/rejected: -2.7390
  • Rewards/accuracies: 0.7242
  • Rewards/margins: 0.9434
  • Logps/rejected: -536.2667
  • Logps/chosen: -447.0530
  • Logits/rejected: 0.9396
  • Logits/chosen: 0.5316

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: 4
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 4
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 64
  • total_eval_batch_size: 32
  • 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
0.6087 0.1 100 0.6158 -0.3136 -0.5466 0.6726 0.2330 -317.0252 -298.8513 -2.0360 -2.1198
0.5463 0.21 200 0.5504 -1.1262 -1.6978 0.6925 0.5716 -432.1413 -380.1157 -0.0431 -0.2986
0.4949 0.31 300 0.5161 -1.6535 -2.4330 0.7183 0.7794 -505.6621 -432.8479 0.4034 0.1418
0.5239 0.42 400 0.5101 -1.3693 -2.0810 0.7302 0.7116 -470.4624 -404.4282 0.8585 0.5591
0.5272 0.52 500 0.5003 -2.0358 -2.9629 0.7381 0.9271 -558.6534 -471.0703 1.0404 0.7150
0.4886 0.63 600 0.4982 -1.7739 -2.6428 0.7262 0.8689 -526.6414 -444.8822 0.3752 0.0594
0.516 0.73 700 0.4933 -2.0243 -2.9388 0.7302 0.9144 -556.2413 -469.9273 0.8898 0.5312
0.495 0.84 800 0.4949 -1.7382 -2.6840 0.7262 0.9458 -530.7620 -441.3121 0.8308 0.4157
0.4866 0.94 900 0.4932 -1.7916 -2.7322 0.7262 0.9407 -535.5854 -446.6503 0.9353 0.5257

Framework versions

  • PEFT 0.7.1
  • Transformers 4.38.2
  • Pytorch 2.1.2+cu121
  • Datasets 2.14.6
  • Tokenizers 0.15.2