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robeczech_lr3e-05_bs16_train30

Token Classification
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metadata
library_name: transformers
license: cc-by-nc-sa-4.0
base_model: ufal/robeczech-base
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: robeczech_lr3e-05_bs16_train30
    results: []

robeczech_lr3e-05_bs16_train30

This model is a fine-tuned version of ufal/robeczech-base on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7524
  • Precision: 0.6957
  • Recall: 0.7042
  • F1: 0.6999
  • Accuracy: 0.8581

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: 3e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • 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: 30

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 1.0 2 2.1827 0.0789 0.0029 0.0056 0.5672
No log 2.0 4 1.8547 0.0 0.0 0.0 0.5666
No log 3.0 6 1.7184 0.0 0.0 0.0 0.5666
No log 4.0 8 1.6366 0.0 0.0 0.0 0.5666
No log 5.0 10 1.5608 0.0 0.0 0.0 0.5666
No log 6.0 12 1.4897 0.0 0.0 0.0 0.5666
No log 7.0 14 1.4198 0.5 0.0048 0.0096 0.5686
No log 8.0 16 1.3505 0.4098 0.0121 0.0235 0.5718
No log 9.0 18 1.2871 0.3481 0.0227 0.0426 0.5764
No log 10.0 20 1.2321 0.3907 0.0526 0.0928 0.5892
No log 11.0 22 1.1821 0.4436 0.1347 0.2067 0.6235
No log 12.0 24 1.1378 0.4340 0.2685 0.3317 0.6789
No log 13.0 26 1.0951 0.4228 0.3317 0.3718 0.7041
No log 14.0 28 1.0571 0.4412 0.3877 0.4127 0.7265
No log 15.0 30 1.0247 0.4677 0.4433 0.4551 0.7461
No log 16.0 32 0.9942 0.5116 0.4915 0.5014 0.7662
No log 17.0 34 0.9657 0.5523 0.5278 0.5398 0.7830
No log 18.0 36 0.9422 0.5946 0.5645 0.5791 0.7997
No log 19.0 38 0.9165 0.6177 0.6007 0.6091 0.8144
No log 20.0 40 0.8933 0.6319 0.6340 0.6329 0.8248
No log 21.0 42 0.8715 0.6493 0.6552 0.6522 0.8336
No log 22.0 44 0.8489 0.6654 0.6644 0.6649 0.8391
No log 23.0 46 0.8303 0.6819 0.6707 0.6762 0.8451
No log 24.0 48 0.8136 0.6873 0.6760 0.6816 0.8472
No log 25.0 50 0.8005 0.6881 0.6871 0.6876 0.8506
No log 26.0 52 0.7916 0.6884 0.6944 0.6913 0.8512
No log 27.0 54 0.7836 0.6913 0.6997 0.6955 0.8529
No log 28.0 56 0.7764 0.6934 0.7001 0.6968 0.8539
No log 29.0 58 0.7714 0.6961 0.7011 0.6986 0.8550
No log 30.0 60 0.7693 0.6984 0.7021 0.7002 0.8560

Framework versions

  • Transformers 4.51.3
  • Pytorch 2.6.0+cu124
  • Datasets 3.6.0
  • Tokenizers 0.21.1