zephyr-7b-dpo-full / README.md
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metadata
license: mit
base_model: HuggingFaceH4/mistral-7b-sft-beta
tags:
  - trl
  - dpo
  - generated_from_trainer
model-index:
  - name: zephyr-7b-dpo-full
    results: []

zephyr-7b-dpo-full

This model is a fine-tuned version of HuggingFaceH4/mistral-7b-sft-beta on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2143
  • Rewards/chosen: -0.8956
  • Rewards/rejected: -1.5167
  • Rewards/accuracies: 0.7031
  • Rewards/margins: 0.6212
  • Logps/rejected: -409.0278
  • Logps/chosen: -346.5983
  • Logits/rejected: -2.4275
  • Logits/chosen: -2.4425

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: 8
  • eval_batch_size: 8
  • seed: 3
  • distributed_type: multi-GPU
  • num_devices: 8
  • 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: 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
0.2667 0.21 100 0.2670 -0.4530 -0.7921 0.6797 0.3391 -336.5636 -302.3352 -2.7593 -2.7741
0.2068 0.42 200 0.2087 -0.8343 -1.3671 0.6836 0.5328 -394.0588 -340.4660 -2.5512 -2.5673
0.2095 0.63 300 0.2233 -0.8384 -1.4377 0.7109 0.5993 -401.1194 -340.8771 -2.4645 -2.4791
0.204 0.84 400 0.2143 -0.8956 -1.5167 0.7031 0.6212 -409.0278 -346.5983 -2.4275 -2.4425

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.2+cu121
  • Datasets 2.14.6
  • Tokenizers 0.14.1