just1nseo's picture
Model save
bf9d83a verified
|
raw
history blame
5.23 kB
metadata
license: apache-2.0
library_name: peft
tags:
  - trl
  - dpo
  - generated_from_trainer
base_model: alignment-handbook/zephyr-7b-sft-full
model-index:
  - name: zephyr-dpop-qlora-gpt4-5e-7-epoch3
    results: []

zephyr-dpop-qlora-gpt4-5e-7-epoch3

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

  • Loss: 1.5707
  • Positive Losses: 8.9081
  • Dpo Losses: 0.6660
  • Rewards/chosen: -0.0431
  • Rewards/rejected: -0.1110
  • Rewards/accuracies: 0.6151
  • Rewards/margins: 0.0679
  • Rewards/margins Max: 0.3167
  • Rewards/margins Min: -0.1568
  • Rewards/margins Std: 0.2111
  • Logps/rejected: -270.2825
  • Logps/chosen: -289.5273
  • Logits/rejected: -2.6606
  • Logits/chosen: -2.7037

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: 4
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • total_train_batch_size: 16
  • 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: 3

Training results

Training Loss Epoch Step Validation Loss Positive Losses Dpo Losses 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
0.6835 0.28 100 0.6965 0.0436 0.6917 0.0092 0.0061 0.5833 0.0030 0.0155 -0.0076 0.0103 -258.5689 -284.3059 -2.8089 -2.8541
0.6367 0.56 200 0.7633 0.6990 0.6863 0.0215 0.0070 0.5873 0.0145 0.0761 -0.0391 0.0511 -258.4836 -283.0695 -2.7779 -2.8224
0.5913 0.85 300 0.9198 2.2041 0.6810 0.0123 -0.0144 0.5714 0.0267 0.1358 -0.0683 0.0899 -260.6202 -283.9922 -2.7412 -2.7853
0.5502 1.13 400 1.0826 3.7846 0.6770 0.0010 -0.0361 0.5754 0.0370 0.1861 -0.0963 0.1243 -262.7899 -285.1261 -2.7113 -2.7545
0.5398 1.41 500 1.1571 4.6567 0.6734 0.0027 -0.0441 0.5833 0.0468 0.2338 -0.1166 0.1549 -263.5918 -284.9548 -2.6935 -2.7368
0.5293 1.69 600 1.2245 5.3740 0.6703 0.0016 -0.0536 0.5913 0.0552 0.2655 -0.1284 0.1752 -264.5410 -285.0616 -2.6767 -2.7201
0.5238 1.97 700 1.3783 6.9387 0.6683 -0.0190 -0.0800 0.6032 0.0610 0.2891 -0.1425 0.1922 -267.1869 -287.1237 -2.6726 -2.7154
0.488 2.25 800 1.4896 8.0964 0.6670 -0.0328 -0.0978 0.6111 0.0650 0.3063 -0.1511 0.2037 -268.9666 -288.5044 -2.6644 -2.7076
0.5027 2.54 900 1.5575 8.7828 0.6661 -0.0416 -0.1091 0.6190 0.0675 0.3151 -0.1563 0.2099 -270.0926 -289.3809 -2.6629 -2.7059
0.4962 2.82 1000 1.5707 8.9081 0.6660 -0.0431 -0.1110 0.6151 0.0679 0.3167 -0.1568 0.2111 -270.2825 -289.5273 -2.6606 -2.7037

Framework versions

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