results / README.md
sm3455's picture
End of training
25b74c0 verified
|
Raw
History Blame Contribute Delete
3.06 kB
metadata
library_name: transformers
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
model-index:
  - name: results
    results: []

results

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

  • Loss: 0.1958
  • Accuracy: 0.9431
  • F1: 0.9434

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: 2e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 64
  • 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: 3
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
0.2569 0.1280 50 0.2415 0.9041 0.8996
0.2055 0.2559 100 0.2228 0.9157 0.9194
0.2424 0.3839 150 0.1831 0.9311 0.9310
0.2092 0.5118 200 0.1808 0.9313 0.9316
0.1878 0.6398 250 0.1993 0.9244 0.9273
0.2077 0.7678 300 0.1705 0.9357 0.9367
0.1937 0.8957 350 0.1847 0.9282 0.9310
0.1448 1.0230 400 0.1701 0.9366 0.9361
0.1034 1.1510 450 0.1763 0.9403 0.9403
0.1395 1.2790 500 0.1854 0.9396 0.9401
0.1141 1.4069 550 0.1774 0.9389 0.9381
0.1323 1.5349 600 0.1716 0.9389 0.9377
0.1824 1.6628 650 0.1866 0.9381 0.9398
0.133 1.7908 700 0.1716 0.9415 0.9414
0.1054 1.9187 750 0.1651 0.944 0.9442
0.0473 2.0461 800 0.1755 0.944 0.9440
0.0458 2.1740 850 0.1917 0.9426 0.9427
0.1082 2.3020 900 0.2014 0.9418 0.9424
0.0621 2.4299 950 0.2019 0.9416 0.9418
0.0773 2.5579 1000 0.1988 0.9412 0.9411
0.1104 2.6859 1050 0.2031 0.9418 0.9413
0.079 2.8138 1100 0.1962 0.9431 0.9432
0.0717 2.9418 1150 0.1958 0.9431 0.9434

Framework versions

  • Transformers 4.54.0
  • Pytorch 2.6.0+cu124
  • Datasets 4.0.0
  • Tokenizers 0.21.2