noditrans_cf_seed-42_1e-3

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

  • Loss: 3.5045
  • Accuracy: 0.3638

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: 0.001
  • train_batch_size: 32
  • eval_batch_size: 64
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 256
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 32000
  • num_epochs: 20.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
6.1088 0.9999 1507 4.5189 0.2802
4.1256 1.9998 3014 4.0763 0.3126
3.9258 2.9998 4521 3.8638 0.3280
3.6941 3.9997 6028 3.7448 0.3395
3.6063 4.9996 7535 3.6613 0.3466
3.5012 5.9995 9042 3.6228 0.3499
3.4402 6.9994 10549 3.5851 0.3539
3.39 8.0 12057 3.5568 0.3571
3.3438 8.9999 13564 3.5526 0.3578
3.3235 9.9998 15071 3.5412 0.3591
3.2829 10.9998 16578 3.5373 0.3591
3.2792 11.9997 18085 3.5322 0.3612
3.241 12.9996 19592 3.5302 0.3605
3.2481 13.9995 21099 3.5215 0.3620
3.2136 14.9994 22606 3.5184 0.3621
3.2254 16.0 24114 3.5266 0.3620
3.1947 16.9999 25621 3.5187 0.3618
3.2102 17.9998 27128 3.5164 0.3630
3.182 18.9998 28635 3.5136 0.3633
3.2009 19.9983 30140 3.5045 0.3638

Framework versions

  • Transformers 4.46.2
  • Pytorch 2.5.1+cu124
  • Datasets 3.2.0
  • Tokenizers 0.20.0
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