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metadata
library_name: transformers
license: apache-2.0
base_model: alignment-handbook/zephyr-7b-sft-full
tags:
  - alignment-handbook
  - trl
  - dpo
  - generated_from_trainer
  - trl
  - dpo
  - generated_from_trainer
datasets:
  - HuggingFaceH4/ultrafeedback_binarized
model-index:
  - name: zephyr-7b-align-scan-3e-07-0.62-polynomial-3.0
    results: []

zephyr-7b-align-scan-3e-07-0.62-polynomial-3.0

This model is a fine-tuned version of alignment-handbook/zephyr-7b-sft-full on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8726
  • Rewards/chosen: -0.1874
  • Rewards/rejected: -1.8304
  • Rewards/accuracies: 0.375
  • Rewards/margins: 1.6430
  • Logps/rejected: -84.0806
  • Logps/chosen: -74.7935
  • Logits/rejected: -2.6285
  • Logits/chosen: -2.6453

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: 3e-07
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 4
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • total_eval_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: polynomial
  • 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
0.6629 0.3484 100 0.6374 0.7586 0.3997 0.3452 0.3589 -80.4837 -73.2678 -2.5455 -2.5615
0.7044 0.6969 200 0.6785 0.6115 0.1187 0.3353 0.4927 -80.9369 -73.5050 -2.5325 -2.5487
0.3945 1.0453 300 0.6975 0.7667 0.1071 0.3552 0.6597 -80.9557 -73.2546 -2.5596 -2.5753
0.3859 1.3937 400 0.7396 1.4671 0.5658 0.3571 0.9013 -80.2158 -72.1250 -2.5834 -2.5995
0.3893 1.7422 500 0.7904 -0.4771 -1.4060 0.3492 0.9290 -83.3962 -75.2607 -2.6499 -2.6659
0.3749 2.0906 600 0.8125 0.5611 -0.4847 0.3631 1.0458 -81.9100 -73.5862 -2.6159 -2.6321
0.3662 2.4390 700 0.8412 -0.6104 -2.0869 0.3651 1.4765 -84.4944 -75.4757 -2.5941 -2.6112
0.3615 2.7875 800 0.8766 -0.9523 -2.5666 0.3611 1.6143 -85.2680 -76.0272 -2.6367 -2.6538

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.0
  • Datasets 2.21.0
  • Tokenizers 0.19.1