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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: 4
  • eval_batch_size: 4
  • seed: 8
  • distributed_type: multi-GPU
  • num_devices: 4
  • total_train_batch_size: 16
  • total_eval_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 50
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss
11.2812 0.0 1 11.5156
5.0938 0.2 62 5.1016
3.5703 0.4 124 3.7161
2.582 0.6 186 2.9010
2.2109 0.8 248 2.5156
1.9824 1.0 310 2.3477
1.8594 1.18 372 2.1960
1.748 1.38 434 2.1667
1.748 1.58 496 2.0195
1.7617 1.78 558 2.0749
1.6582 1.98 620 1.9095
1.5762 2.16 682 1.9036
1.5586 2.36 744 1.8457
1.6016 2.56 806 1.8112
1.5195 2.76 868 1.8034
1.5645 2.96 930 1.7773
1.457 3.14 992 1.7474
1.4883 3.34 1054 1.7467
1.4648 3.54 1116 1.7676
1.5195 3.74 1178 1.7383
1.4531 3.94 1240 1.7383
1.4648 4.12 1302 1.7181
1.4121 4.32 1364 1.7272
1.4727 4.52 1426 1.7259
1.4219 4.72 1488 1.7240
1.5137 4.92 1550 1.7227

Framework versions

  • Transformers 4.37.0.dev0
  • Pytorch 2.1.2+cu121
  • Datasets 2.15.0
  • Tokenizers 0.15.0

Built with Axolotl

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Dataset used to train TRAC-MTRY/traclm-v1-3b-instruct