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ABSA-SentencePair-domainAdapt-SemEval-Adapter-pfeiffer_madx-run2

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metadata
license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: ABSA-SentencePair-domainAdapt-SemEval-Adapter-pfeiffer_madx-run2
    results: []

ABSA-SentencePair-domainAdapt-SemEval-Adapter-pfeiffer_madx-run2

This model is a fine-tuned version of CAMeL-Lab/bert-base-arabic-camelbert-msa on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3666
  • Accuracy: 0.8603
  • F1: 0.8603
  • Precision: 0.8603
  • Recall: 0.8603

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: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy F1 Precision Recall
0.5161 1.0 206 0.3972 0.8633 0.8633 0.8633 0.8633
0.3989 2.0 412 0.3739 0.8670 0.8670 0.8670 0.8670
0.3725 3.0 618 0.3870 0.8615 0.8615 0.8615 0.8615
0.3503 4.0 824 0.3892 0.8609 0.8609 0.8609 0.8609
0.3313 5.0 1030 0.3743 0.8682 0.8682 0.8682 0.8682
0.3118 6.0 1236 0.3666 0.8603 0.8603 0.8603 0.8603
0.2982 7.0 1442 0.3972 0.8621 0.8621 0.8621 0.8621
0.2854 8.0 1648 0.4064 0.8335 0.8335 0.8335 0.8335
0.2723 9.0 1854 0.3981 0.8505 0.8505 0.8505 0.8505
0.2641 10.0 2060 0.4067 0.8481 0.8481 0.8481 0.8481
0.2507 11.0 2266 0.4130 0.8439 0.8439 0.8439 0.8439
0.2518 12.0 2472 0.4023 0.8499 0.8499 0.8499 0.8499
0.2387 13.0 2678 0.4123 0.8451 0.8451 0.8451 0.8451
0.2304 14.0 2884 0.4369 0.8560 0.8560 0.8560 0.8560
0.2258 15.0 3090 0.4453 0.8384 0.8384 0.8384 0.8384
0.2258 16.0 3296 0.4272 0.8433 0.8433 0.8433 0.8433
0.2185 17.0 3502 0.4482 0.8420 0.8420 0.8420 0.8420
0.2097 18.0 3708 0.4532 0.8414 0.8414 0.8414 0.8414
0.2069 19.0 3914 0.4580 0.8439 0.8439 0.8439 0.8439
0.2072 20.0 4120 0.4556 0.8433 0.8433 0.8433 0.8433

Framework versions

  • Transformers 4.26.1
  • Pytorch 2.0.1+cu118
  • Datasets 2.13.1
  • Tokenizers 0.13.3