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roberta-base-downstream-build_rr

Token Classification
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roberta
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metadata
library_name: transformers
license: mit
base_model: roberta-base
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: roberta-base-downstream-build_rr
    results: []

roberta-base-downstream-build_rr

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

  • Loss: 0.8272
  • Precision-macro: 0.6089
  • Recall-macro: 0.5868
  • Macro-f1: 0.5926
  • Precision-micro: 0.7798
  • Recall-micro: 0.7798
  • Micro-f1: 0.7798
  • Accuracy: 0.7798

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: 4
  • eval_batch_size: 4
  • seed: 1
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Precision-macro Recall-macro Macro-f1 Precision-micro Recall-micro Micro-f1 Accuracy
No log 1.0 62 1.1797 0.3651 0.2425 0.2406 0.6509 0.6509 0.6509 0.6509
No log 2.0 124 0.8354 0.5350 0.5291 0.5255 0.7350 0.7350 0.7350 0.7350
No log 3.0 186 0.8058 0.5559 0.5382 0.5366 0.7343 0.7343 0.7343 0.7343
No log 4.0 248 0.7718 0.6246 0.5201 0.5300 0.7503 0.7503 0.7503 0.7503
No log 5.0 310 0.7307 0.5890 0.5463 0.5579 0.7642 0.7642 0.7642 0.7642
No log 6.0 372 0.7099 0.6076 0.5431 0.5481 0.7746 0.7746 0.7746 0.7746
No log 7.0 434 0.7072 0.6090 0.5126 0.5261 0.7812 0.7812 0.7812 0.7812
No log 8.0 496 0.6919 0.6321 0.5471 0.5676 0.7826 0.7826 0.7826 0.7826
0.8758 9.0 558 0.7503 0.5666 0.5818 0.5696 0.7735 0.7735 0.7735 0.7735
0.8758 10.0 620 0.7512 0.6054 0.5656 0.5755 0.7784 0.7784 0.7784 0.7784
0.8758 11.0 682 0.7656 0.6086 0.5835 0.5913 0.7829 0.7829 0.7829 0.7829
0.8758 12.0 744 0.7861 0.5972 0.5885 0.5843 0.7739 0.7739 0.7739 0.7739
0.8758 13.0 806 0.8239 0.5975 0.5749 0.5701 0.7780 0.7780 0.7780 0.7780
0.8758 14.0 868 0.8272 0.6089 0.5868 0.5926 0.7798 0.7798 0.7798 0.7798

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.0+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1