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metadata
library_name: peft
tags:
  - alignment-handbook
  - trl
  - dpo
  - generated_from_trainer
base_model: NbAiLab/nb-gpt-j-6B-v2
datasets:
  - hugodk-sch/aftonposten_title_prefs
model-index:
  - name: aftonposten-6b-align-scan
    results: []

aftonposten-6b-align-scan

This model is a fine-tuned version of data/ap-gpt-j-6b-sft-qlora-04-08 on the hugodk-sch/aftonposten_title_prefs dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4937
  • Rewards/chosen: 0.2548
  • Rewards/rejected: 0.2285
  • Rewards/accuracies: 0.5274
  • Rewards/margins: 0.0263
  • Logps/rejected: -37.2627
  • Logps/chosen: -33.7514
  • Logits/rejected: -2.2263
  • Logits/chosen: -2.2311

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: 4
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 8
  • 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
0.4639 0.26 100 0.4939 0.1483 0.1205 0.5627 0.0278 -37.3828 -33.8698 -2.2305 -2.2354
0.4308 0.52 200 0.4894 0.2606 0.2153 0.5544 0.0453 -37.2774 -33.7450 -2.2290 -2.2338
0.374 0.78 300 0.4904 0.2570 0.2171 0.5220 0.0399 -37.2754 -33.7490 -2.2259 -2.2308

Framework versions

  • PEFT 0.8.2
  • Transformers 4.37.2
  • Pytorch 2.1.2+cu121
  • Datasets 2.17.0
  • Tokenizers 0.15.1