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lambda-gemma-2-9b-dpo

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lambda-gemma-2-9b-dpo / README.md
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metadata
license: gemma
tags:
  - alignment-handbook
  - trl
  - dpo
  - generated_from_trainer
  - trl
  - dpo
  - generated_from_trainer
base_model: tanliboy/zephyr-gemma-2-9b-sft
datasets:
  - HuggingFaceH4/ultrafeedback_binarized
model-index:
  - name: zephyr-gemma-2-9b-dpo-2
    results: []

Visualize in Weights & Biases

zephyr-gemma-2-9b-dpo-2

This model is a fine-tuned version of tanliboy/zephyr-gemma-2-9b-sft on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5628
  • Rewards/chosen: -0.7292
  • Rewards/rejected: -1.2825
  • Rewards/accuracies: 0.6960
  • Rewards/margins: 0.5533
  • Logps/rejected: -1566.9301
  • Logps/chosen: -1043.5624
  • Logits/rejected: -14.1720
  • Logits/chosen: -14.6638

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: 2
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • gradient_accumulation_steps: 16
  • total_train_batch_size: 256
  • 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: 0.2
  • 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
0.6835 0.2094 50 0.6815 -0.0218 -0.0436 0.6560 0.0218 -328.0053 -336.0947 -11.6381 -11.3403
0.6243 0.4187 100 0.6229 -0.5238 -0.7528 0.6600 0.2290 -1037.2136 -838.1255 -15.5098 -15.6787
0.5625 0.6281 150 0.5793 -0.7186 -1.1873 0.6880 0.4688 -1471.7362 -1032.8834 -14.7746 -15.1797
0.5699 0.8375 200 0.5647 -0.6443 -1.1499 0.6920 0.5057 -1434.3335 -958.5825 -14.1861 -14.6684

Framework versions

  • Transformers 4.43.1
  • Pytorch 2.3.1+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric Value
Avg. 21.34
IFEval (0-Shot) 45.01
BBH (3-Shot) 35.55
MATH Lvl 5 (4-Shot) 0.00
GPQA (0-shot) 8.50
MuSR (0-shot) 7.94
MMLU-PRO (5-shot) 31.02