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phi2-samsum

This model is a fine-tuned version of microsoft/phi-2 on the samsum dataset. It achieves the following results on the evaluation set:

  • Loss: 2.2606

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: 2.5e-05
  • train_batch_size: 2
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 1
  • training_steps: 500

Training results

Training Loss Epoch Step Validation Loss
2.7371 0.0 25 2.5507
2.5853 0.01 50 2.3917
2.3176 0.01 75 2.3258
2.3459 0.01 100 2.3066
2.3003 0.02 125 2.2957
2.2767 0.02 150 2.2883
2.2637 0.02 175 2.2835
2.3387 0.03 200 2.2787
2.3151 0.03 225 2.2759
2.1807 0.03 250 2.2767
2.4122 0.04 275 2.2703
2.139 0.04 300 2.2680
2.3887 0.04 325 2.2664
2.2124 0.05 350 2.2648
2.2271 0.05 375 2.2649
2.3335 0.05 400 2.2634
2.2411 0.06 425 2.2628
2.4075 0.06 450 2.2619
2.3136 0.06 475 2.2615
2.2328 0.07 500 2.2606

Framework versions

  • PEFT 0.7.2.dev0
  • Transformers 4.38.0.dev0
  • Pytorch 2.1.0+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.0
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Dataset used to train vgorce/phi2-samsum