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metadata
library_name: peft
tags:
  - alignment-handbook
  - trl
  - dpo
  - generated_from_trainer
base_model: NorLLM-AI/NorMistral-7B
datasets:
  - hugodk-sch/aftonposten_title_prefs
model-index:
  - name: norllm-ai-normistral-7b-align-scan
    results: []

norllm-ai-normistral-7b-align-scan

This model is a fine-tuned version of data/norllm-ai-normistral-7b-sft-qlora on the hugodk-sch/aftonposten_title_prefs dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9008
  • Rewards/chosen: -0.1005
  • Rewards/rejected: -0.2216
  • Rewards/accuracies: 0.5860
  • Rewards/margins: 0.1211
  • Logps/rejected: -34.9752
  • Logps/chosen: -31.4081
  • Logits/rejected: -2.8074
  • Logits/chosen: -2.8099

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
0.8401 0.26 100 0.8873 0.0047 -0.1245 0.6067 0.1292 -34.8538 -31.2766 -2.8093 -2.8118
0.724 0.52 200 0.9140 -0.0857 -0.1841 0.5656 0.0983 -34.9282 -31.3896 -2.8156 -2.8179
0.6408 0.78 300 0.9091 -0.0880 -0.2014 0.5627 0.1135 -34.9500 -31.3924 -2.8077 -2.8102

Framework versions

  • PEFT 0.10.0
  • Transformers 4.39.0.dev0
  • Pytorch 2.1.2+cu121
  • Datasets 2.14.6
  • Tokenizers 0.15.1