m-minilm-l12-h384-dra-tam-mal-aw-setfit-double-finetune

This model is a fine-tuned version of livinNector/m-minilm-l12-h384-dra-tam-mal-aw-setfit-finetune on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5252
  • Accuracy: 0.7759
  • F1: 0.7752

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: 0.0001
  • train_batch_size: 128
  • eval_batch_size: 128
  • seed: 42
  • 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
  • num_epochs: 6

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
0.6682 0.4444 20 0.6228 0.6659 0.6625
0.6171 0.8889 40 0.6035 0.6789 0.6756
0.5673 1.3333 60 0.5673 0.7188 0.7155
0.5481 1.7778 80 0.5864 0.6993 0.6937
0.5137 2.2222 100 0.5245 0.7465 0.7440
0.4527 2.6667 120 0.5279 0.7522 0.7506
0.4596 3.1111 140 0.5172 0.7579 0.7576
0.3943 3.5556 160 0.5366 0.7514 0.7514
0.3836 4.0 180 0.5387 0.7628 0.7627
0.3627 4.4444 200 0.5802 0.7490 0.7480
0.3302 4.8889 220 0.5616 0.7563 0.7563
0.2999 5.3333 240 0.5745 0.7620 0.7598
0.3061 5.7778 260 0.5651 0.7694 0.7689

Framework versions

  • Transformers 4.47.1
  • Pytorch 2.5.1+cu124
  • Datasets 3.2.0
  • Tokenizers 0.21.0
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