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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:
  - data/conifer
model-index:
  - name: rlced_conifer_zephyr-7b-dpo-full
    results: []

rlced_conifer_zephyr-7b-dpo-full

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

  • Loss: 0.2006
  • Rewards/chosen: -4.0000
  • Rewards/rejected: -11.3920
  • Rewards/accuracies: 0.8687
  • Rewards/margins: 7.3920
  • Logps/rejected: -1507.9508
  • Logps/chosen: -760.1741
  • Logits/rejected: -1.6795
  • Logits/chosen: -2.0969

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: 8
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 256
  • total_eval_batch_size: 64
  • 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
0.2558 0.2107 100 0.2515 -3.3402 -7.6336 0.8363 4.2934 -1132.1079 -694.1878 -3.1129 -3.1245
0.2204 0.4215 200 0.2260 -3.7625 -9.3814 0.8587 5.6190 -1306.8950 -736.4189 -2.6948 -2.7329
0.204 0.6322 300 0.2096 -3.3959 -9.7494 0.8650 6.3535 -1343.6858 -699.7554 -2.1723 -2.4109
0.1992 0.8430 400 0.2007 -4.2176 -11.7584 0.8650 7.5408 -1544.5891 -781.9304 -1.6459 -2.0690

Framework versions

  • Transformers 4.44.1
  • Pytorch 2.1.2+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1