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: 0.9294
  • Rewards/chosen: -0.0900
  • Rewards/rejected: -0.1614
  • Rewards/accuracies: 0.6009
  • Rewards/margins: 0.0715
  • Logps/rejected: -35.5053
  • Logps/chosen: -31.7323
  • Logits/rejected: -2.8259
  • Logits/chosen: -2.8279

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
0.9239 0.26 100 0.9661 -0.0010 -0.0351 0.6013 0.0342 -34.8738 -31.2872 -2.8027 -2.8055
0.8146 0.52 200 0.9363 -0.0747 -0.1389 0.6184 0.0641 -35.3925 -31.6561 -2.8206 -2.8233
0.7173 0.78 300 0.9279 -0.0837 -0.1567 0.6125 0.0730 -35.4817 -31.7010 -2.8247 -2.8267

Framework versions

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