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

zephyr-7b-dpo-lora

This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5270
  • Rewards/chosen: -0.1210
  • Rewards/rejected: -0.9978
  • Rewards/accuracies: 0.7812
  • Rewards/margins: 0.8768
  • Logps/rejected: -198.5849
  • Logps/chosen: -248.6519
  • Logits/rejected: -1.9190
  • Logits/chosen: -2.0860

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: 32
  • total_train_batch_size: 64
  • total_eval_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss Rewards/chosen Rewards/rejected Rewards/accuracies Rewards/margins Logps/rejected Logps/chosen Logits/rejected Logits/chosen
0.5491 1.0 969 0.5563 -0.0962 -0.7226 0.7812 0.6263 -195.8333 -248.4046 -1.9755 -2.1375
0.5454 2.0 1938 0.5312 -0.1249 -0.9600 0.7969 0.8351 -198.2077 -248.6910 -1.9316 -2.0971
0.5242 3.0 2907 0.5270 -0.1210 -0.9978 0.7812 0.8768 -198.5849 -248.6519 -1.9190 -2.0860

Framework versions

  • Transformers 4.35.0
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.6
  • Tokenizers 0.14.1