phi3-spin-phi3-data

This model is a fine-tuned version of microsoft/Phi-3-small-8k-instruct on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0000
  • Rewards/real: -20.4314
  • Rewards/generated: -59.7851
  • Rewards/accuracies: 1.0
  • Rewards/margins: 39.3538
  • Logps/generated: -1415.6521
  • Logps/real: -459.2887
  • Logits/generated: -inf
  • Logits/real: -inf

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-07
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 4
  • total_train_batch_size: 32
  • total_eval_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss Rewards/real Rewards/generated Rewards/accuracies Rewards/margins Logps/generated Logps/real Logits/generated Logits/real
0.0013 0.32 500 0.0028 -15.0276 -43.9108 1.0 28.8832 -1256.9089 -405.2515 -inf -inf
0.0007 0.64 1000 0.0001 -20.5002 -56.1393 1.0 35.6391 -1379.1938 -459.9772 -inf -inf
0.0081 0.96 1500 0.0000 -20.4314 -59.7851 1.0 39.3538 -1415.6521 -459.2887 -inf -inf

Framework versions

  • Transformers 4.37.0
  • Pytorch 2.1.2+cu121
  • Datasets 2.14.6
  • Tokenizers 0.15.2
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