simpo / README.md
jz666's picture
End of training
5402950 verified
metadata
library_name: transformers
license: gemma
base_model: google/gemma-2-9b-it
tags:
  - alignment-handbook
  - trl
  - simpo
  - generated_from_trainer
  - trl
  - simpo
  - generated_from_trainer
datasets:
  - princeton-nlp/gemma2-ultrafeedback-armorm
model-index:
  - name: simpo
    results: []

simpo

This model is a fine-tuned version of google/gemma-2-9b-it on the princeton-nlp/gemma2-ultrafeedback-armorm dataset. It achieves the following results on the evaluation set:

  • Loss: 2.7459
  • Rewards/chosen: -18.9664
  • Rewards/rejected: -23.9949
  • Rewards/accuracies: 0.7725
  • Rewards/margins: 5.0285
  • Logps/rejected: -2.3995
  • Logps/chosen: -1.8966
  • Logits/rejected: -14.4878
  • Logits/chosen: -14.5537

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: 8e-07
  • train_batch_size: 2
  • eval_batch_size: 4
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 4
  • gradient_accumulation_steps: 16
  • total_train_batch_size: 128
  • total_eval_batch_size: 16
  • 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
2.7196 0.8594 400 2.7580 -18.9526 -23.9387 0.7705 4.9861 -2.3939 -1.8953 -14.4321 -14.5024

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.7.0+cu128
  • Datasets 2.18.0
  • Tokenizers 0.19.1