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gshf_lora_iter_3

This model is a fine-tuned version of YYYYYYibo/gshf_lora_iter_2 on the updated and the original datasets. It achieves the following results on the evaluation set:

  • Loss: 0.6864
  • Rewards/chosen: -1.0331
  • Rewards/rejected: -1.1393
  • Rewards/accuracies: 0.5780
  • Rewards/margins: 0.1061
  • Logps/rejected: -401.6631
  • Logps/chosen: -412.7206
  • Logits/rejected: -2.2917
  • Logits/chosen: -2.4065

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: 2
  • eval_batch_size: 2
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 4
  • gradient_accumulation_steps: 16
  • total_train_batch_size: 128
  • total_eval_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
0.5977 0.61 100 0.6864 -1.0331 -1.1393 0.5780 0.1061 -401.6631 -412.7206 -2.2917 -2.4065

Framework versions

  • PEFT 0.7.1
  • Transformers 4.36.2
  • Pytorch 2.1.2+cu121
  • Datasets 2.14.6
  • Tokenizers 0.15.2
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