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vicuna-adv-robust-u50-sft-lora

This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.2125

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: 0.0003
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 4
  • gradient_accumulation_steps: 16
  • total_train_batch_size: 512
  • total_eval_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • num_epochs: 50

Training results

Training Loss Epoch Step Validation Loss
No log 0 0 2.4952
2.5615 1.09 1 2.5270
2.5615 1.09 1 2.5362
2.5615 3.03 2 2.5342
2.5615 4.12 3 2.2735
2.5615 4.12 3 2.3209
2.5615 6.06 4 2.1017
2.363 7.15 5 2.0121
2.363 7.15 5 2.0751
2.363 9.09 6 1.9646
2.363 9.09 6 1.8912
2.363 11.03 7 1.8100
2.363 12.12 8 1.8144
2.363 12.12 8 1.7983
2.363 14.06 9 1.7634
1.9009 15.15 10 1.7628
1.9009 15.15 10 1.7354
1.9009 17.09 11 1.7343
1.9009 17.09 11 1.7232
1.9009 19.03 12 1.6737
1.9009 20.12 13 1.6418
1.9009 20.12 13 1.6635
1.9009 22.06 14 1.6280
1.7031 23.15 15 1.6042
1.7031 23.15 15 1.6120
1.7031 25.09 16 1.5792
1.7031 25.09 16 1.6128
1.7031 27.03 17 1.5468
1.7031 28.12 18 1.5303
1.7031 28.12 18 1.5160
1.7031 30.06 19 1.5195
1.5968 31.15 20 1.5098
1.5968 31.15 20 1.4775
1.5968 33.09 21 1.4770
1.5968 33.09 21 1.4588
1.5968 35.03 22 1.4474
1.5968 36.12 23 1.4240
1.5968 36.12 23 1.4164
1.5968 38.06 24 1.4060
1.4776 39.15 25 1.3753
1.4776 39.15 25 1.3858
1.4776 41.09 26 1.3822
1.4776 41.09 26 1.3268
1.4776 43.03 27 1.3443
1.4776 44.12 28 1.3259
1.4776 44.12 28 1.3117
1.4776 46.06 29 1.3105
1.3585 47.15 30 1.2553
1.3585 47.15 30 1.2755
1.3585 49.09 31 1.2036

Framework versions

  • Transformers 4.35.0
  • Pytorch 2.1.0a0+32f93b1
  • Datasets 2.14.6
  • Tokenizers 0.14.1
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