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metadata
license: other
library_name: peft
tags:
  - alignment-handbook
  - trl
  - dpo
  - generated_from_trainer
base_model: meta-llama/Meta-Llama-3-8B
datasets:
  - EllieS/Temp-L2-DPO
model-index:
  - name: llama3-L1-SFT-L2-DPO
    results: []

llama3-L1-SFT-L2-DPO

This model is a fine-tuned version of EllieS/TempReason-L1-llama3 on the EllieS/Temp-L2-DPO dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0028
  • Rewards/chosen: -0.4016
  • Rewards/rejected: -9.3312
  • Rewards/accuracies: 1.0
  • Rewards/margins: 8.9296
  • Logps/rejected: -994.2072
  • Logps/chosen: -84.5141
  • Logits/rejected: 1.5698
  • Logits/chosen: 0.6541

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: 1
  • eval_batch_size: 1
  • seed: 42
  • distributed_type: multi-GPU
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 4
  • 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
0.0033 0.2497 1000 0.0065 -0.3610 -7.6953 1.0 7.3344 -830.6234 -80.4518 1.5489 0.7452
0.0013 0.4995 2000 0.0031 -0.3798 -9.1892 1.0 8.8094 -980.0131 -82.3365 1.5546 0.6455
0.0019 0.7492 3000 0.0028 -0.3966 -9.3440 1.0 8.9474 -995.4902 -84.0208 1.5703 0.6568
0.0011 0.9989 4000 0.0028 -0.4016 -9.3312 1.0 8.9296 -994.2072 -84.5141 1.5698 0.6541

Framework versions

  • PEFT 0.7.1
  • Transformers 4.40.2
  • Pytorch 2.1.2+cu121
  • Datasets 2.18.0
  • Tokenizers 0.19.1