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Mistral-7B-Instruct-v0.3-dpo-lora_lr1e-5_5ep

This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.3 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2423
  • Rewards/chosen: -0.5640
  • Rewards/rejected: -4.3641
  • Rewards/accuracies: 0.8557
  • Rewards/margins: 3.8002
  • Logps/rejected: -417.8773
  • Logps/chosen: -434.6749
  • Logits/rejected: 0.0188
  • Logits/chosen: 0.1716

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: 1e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.05
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss Rewards/chosen Rewards/rejected Rewards/accuracies Rewards/margins Logps/rejected Logps/chosen Logits/rejected Logits/chosen
0.4274 1.0 103 0.3324 0.2097 -1.9397 0.7932 2.1493 -393.6328 -426.9386 -0.3230 -0.0880
0.1309 2.0 206 0.2679 0.0296 -2.9700 0.8482 2.9997 -403.9364 -428.7391 -0.1288 0.0588
0.0376 3.0 309 0.2491 -0.4817 -4.1509 0.8452 3.6692 -415.7445 -433.8520 -0.0034 0.1539
0.0158 4.0 412 0.2450 -0.5678 -4.3787 0.8557 3.8110 -418.0231 -434.7127 0.0183 0.1715
0.0129 5.0 515 0.2423 -0.5640 -4.3641 0.8557 3.8002 -417.8773 -434.6749 0.0188 0.1716

Framework versions

  • PEFT 0.11.1
  • Transformers 4.41.1
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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