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POEMS-CAMELBERT-CA-RUN4-25

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metadata
license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
base_model: CAMeL-Lab/bert-base-arabic-camelbert-ca
model-index:
  - name: POEMS-CAMELBERT-CA-RUN4-25
    results: []

POEMS-CAMELBERT-CA-RUN4-25

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

  • Loss: 1.7725
  • Accuracy: 0.5731
  • F1: 0.5731
  • Precision: 0.5731
  • Recall: 0.5731

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: 5e-05
  • 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: 25

Training results

Training Loss Epoch Step Validation Loss Accuracy F1 Precision Recall
1.3427 1.0 472 1.2734 0.4056 0.4056 0.4056 0.4056
1.1941 2.0 944 1.1317 0.5129 0.5129 0.5129 0.5129
1.1178 3.0 1416 1.1461 0.5142 0.5142 0.5142 0.5142
1.0569 4.0 1888 1.0592 0.5412 0.5412 0.5412 0.5412
0.9925 5.0 2360 1.1219 0.5426 0.5426 0.5426 0.5426
0.9375 6.0 2832 1.0840 0.5740 0.5740 0.5740 0.5740
0.8771 7.0 3304 1.1091 0.5816 0.5816 0.5816 0.5816
0.8262 8.0 3776 1.1221 0.5851 0.5851 0.5851 0.5851
0.7871 9.0 4248 1.1499 0.5745 0.5745 0.5745 0.5745
0.7252 10.0 4720 1.3011 0.5621 0.5621 0.5621 0.5621
0.6919 11.0 5192 1.3272 0.5802 0.5802 0.5802 0.5802
0.6427 12.0 5664 1.3928 0.5683 0.5683 0.5683 0.5683
0.6008 13.0 6136 1.4789 0.5590 0.5590 0.5590 0.5590
0.5576 14.0 6608 1.4850 0.5638 0.5638 0.5638 0.5638
0.5267 15.0 7080 1.5124 0.5762 0.5762 0.5762 0.5762
0.4823 16.0 7552 1.3870 0.5683 0.5683 0.5683 0.5683
0.4564 17.0 8024 1.5277 0.5785 0.5785 0.5785 0.5785
0.4217 18.0 8496 1.5805 0.5723 0.5723 0.5723 0.5723
0.3891 19.0 8968 1.5173 0.5709 0.5709 0.5709 0.5709
0.3705 20.0 9440 1.6484 0.5807 0.5807 0.5807 0.5807
0.3419 21.0 9912 1.6999 0.5816 0.5816 0.5816 0.5816
0.321 22.0 10384 1.7024 0.5745 0.5745 0.5745 0.5745
0.3121 23.0 10856 1.7545 0.5709 0.5709 0.5709 0.5709
0.2964 24.0 11328 1.7355 0.5767 0.5767 0.5767 0.5767
0.285 25.0 11800 1.7725 0.5731 0.5731 0.5731 0.5731

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2