Hugging Face's logo

MayBashendy
/
arabert_baseline_organization_task1_fold1

Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
arabert_baseline_organization_task1_fold1 / README.md
MayBashendy's picture
MayBashendy
End of training
2ae78e9 verified
preview code
|
raw
history blame contribute delete
5.83 kB
metadata
library_name: transformers
base_model: aubmindlab/bert-base-arabertv02
tags:
  - generated_from_trainer
model-index:
  - name: arabert_baseline_organization_task1_fold1
    results: []

arabert_baseline_organization_task1_fold1

This model is a fine-tuned version of aubmindlab/bert-base-arabertv02 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7406
  • Qwk: 0.7336
  • Mse: 0.7406
  • Rmse: 0.8606

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: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Qwk Mse Rmse
No log 0.1818 2 3.0376 0.0094 3.0376 1.7429
No log 0.3636 4 1.6849 -0.0143 1.6849 1.2980
No log 0.5455 6 1.2236 0.0597 1.2236 1.1061
No log 0.7273 8 1.2683 -0.0302 1.2683 1.1262
No log 0.9091 10 1.1217 -0.0161 1.1217 1.0591
No log 1.0909 12 0.9264 -0.0467 0.9264 0.9625
No log 1.2727 14 0.8294 -0.0284 0.8294 0.9107
No log 1.4545 16 0.8008 0.0427 0.8008 0.8949
No log 1.6364 18 0.7784 0.0427 0.7784 0.8823
No log 1.8182 20 0.7216 0.0 0.7216 0.8495
No log 2.0 22 0.7271 0.2857 0.7271 0.8527
No log 2.1818 24 0.7480 0.3090 0.7480 0.8649
No log 2.3636 26 0.6967 0.3109 0.6967 0.8347
No log 2.5455 28 0.6857 0.4 0.6857 0.8281
No log 2.7273 30 0.6479 0.5926 0.6479 0.8049
No log 2.9091 32 0.6868 0.5926 0.6868 0.8287
No log 3.0909 34 0.6055 0.6316 0.6055 0.7781
No log 3.2727 36 0.5330 0.5776 0.5330 0.7301
No log 3.4545 38 0.4870 0.6345 0.4870 0.6979
No log 3.6364 40 0.5030 0.6638 0.5030 0.7093
No log 3.8182 42 0.4888 0.5767 0.4888 0.6991
No log 4.0 44 0.4738 0.5767 0.4738 0.6884
No log 4.1818 46 0.5713 0.6410 0.5713 0.7559
No log 4.3636 48 0.7034 0.7482 0.7034 0.8387
No log 4.5455 50 0.7505 0.7426 0.7505 0.8663
No log 4.7273 52 0.7736 0.7426 0.7736 0.8796
No log 4.9091 54 0.6137 0.7390 0.6137 0.7834
No log 5.0909 56 0.6615 0.7390 0.6615 0.8133
No log 5.2727 58 0.8090 0.7138 0.8090 0.8995
No log 5.4545 60 0.7775 0.7287 0.7775 0.8818
No log 5.6364 62 0.6471 0.7107 0.6471 0.8045
No log 5.8182 64 0.5071 0.6547 0.5071 0.7121
No log 6.0 66 0.4469 0.6500 0.4469 0.6685
No log 6.1818 68 0.4640 0.6866 0.4640 0.6812
No log 6.3636 70 0.6052 0.7266 0.6052 0.7779
No log 6.5455 72 0.8728 0.6873 0.8728 0.9342
No log 6.7273 74 0.9762 0.7219 0.9762 0.9880
No log 6.9091 76 0.8461 0.6873 0.8461 0.9198
No log 7.0909 78 0.6379 0.7181 0.6379 0.7987
No log 7.2727 80 0.5480 0.6839 0.5480 0.7403
No log 7.4545 82 0.5355 0.6839 0.5355 0.7318
No log 7.6364 84 0.5699 0.7162 0.5699 0.7549
No log 7.8182 86 0.6654 0.6915 0.6654 0.8157
No log 8.0 88 0.8127 0.7 0.8127 0.9015
No log 8.1818 90 0.8907 0.7 0.8907 0.9438
No log 8.3636 92 0.8716 0.7 0.8716 0.9336
No log 8.5455 94 0.8174 0.72 0.8174 0.9041
No log 8.7273 96 0.7611 0.7336 0.7611 0.8724
No log 8.9091 98 0.7738 0.7336 0.7738 0.8797
No log 9.0909 100 0.7710 0.7336 0.7710 0.8781
No log 9.2727 102 0.7508 0.7336 0.7508 0.8665
No log 9.4545 104 0.7428 0.7336 0.7428 0.8619
No log 9.6364 106 0.7452 0.7336 0.7452 0.8633
No log 9.8182 108 0.7414 0.7336 0.7414 0.8611
No log 10.0 110 0.7406 0.7336 0.7406 0.8606

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.0+cu118
  • Datasets 2.21.0
  • Tokenizers 0.19.1