ap-normistral-7b-align-scan

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

  • Loss: 0.9524
  • Rewards/chosen: -0.0816
  • Rewards/rejected: -0.1313
  • Rewards/accuracies: 0.5303
  • Rewards/margins: 0.0497
  • Logps/rejected: -36.6233
  • Logps/chosen: -32.8513
  • Logits/rejected: 98.1886
  • Logits/chosen: 98.2171

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
0.927 0.26 100 0.9734 0.0205 -0.0061 0.5598 0.0265 -35.9968 -32.3408 98.7115 98.7190
0.7448 0.52 200 0.9482 -0.0840 -0.1367 0.5307 0.0527 -36.6501 -32.8631 98.2057 98.2271
0.7402 0.78 300 0.9400 -0.0802 -0.1425 0.5623 0.0624 -36.6792 -32.8440 98.1900 98.2178

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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