Hugging Face's logo

MayBashendy
/
Arabic_FineTuningAraBERT_AugV0_k1_task1_organization_fold0

Text Classification
Transformers
Safetensors
bert
Generated from Trainer
Inference Endpoints
Model card Files Community
Arabic_FineTuningAraBERT_AugV0_k1_task1_organization_fold0 / README.md
MayBashendy's picture
MayBashendy
End of training
bb0a253 verified
preview code
|
raw
history blame contribute delete
8.18 kB
metadata
library_name: transformers
base_model: aubmindlab/bert-base-arabertv02
tags:
  - generated_from_trainer
model-index:
  - name: Arabic_FineTuningAraBERT_AugV0_k1_task1_organization_fold0
    results: []

Arabic_FineTuningAraBERT_AugV0_k1_task1_organization_fold0

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: 0.9449
  • Qwk: 0.5896
  • Mse: 0.9449
  • Rmse: 0.9721

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 0.1176 2 5.1330 0.0904 5.1330 2.2656
No log 0.2353 4 3.4675 0.0 3.4675 1.8621
No log 0.3529 6 2.3648 0.0696 2.3648 1.5378
No log 0.4706 8 1.6993 0.0 1.6993 1.3036
No log 0.5882 10 1.4000 0.1973 1.4000 1.1832
No log 0.7059 12 1.3257 0.1933 1.3257 1.1514
No log 0.8235 14 1.2645 0.2939 1.2645 1.1245
No log 0.9412 16 1.2126 0.2668 1.2126 1.1012
No log 1.0588 18 0.9516 0.3259 0.9516 0.9755
No log 1.1765 20 0.8599 0.4590 0.8599 0.9273
No log 1.2941 22 0.8162 0.4085 0.8162 0.9035
No log 1.4118 24 0.9496 0.3478 0.9496 0.9745
No log 1.5294 26 1.1079 0.3209 1.1079 1.0526
No log 1.6471 28 1.1311 0.3209 1.1311 1.0635
No log 1.7647 30 1.0768 0.3494 1.0768 1.0377
No log 1.8824 32 1.0150 0.5698 1.0150 1.0075
No log 2.0 34 1.0474 0.5468 1.0474 1.0234
No log 2.1176 36 0.9894 0.5653 0.9894 0.9947
No log 2.2353 38 0.8745 0.5830 0.8745 0.9351
No log 2.3529 40 0.8798 0.6738 0.8798 0.9380
No log 2.4706 42 1.0482 0.5830 1.0482 1.0238
No log 2.5882 44 1.1713 0.5660 1.1713 1.0823
No log 2.7059 46 1.0797 0.5686 1.0797 1.0391
No log 2.8235 48 0.9651 0.5686 0.9651 0.9824
No log 2.9412 50 0.8528 0.6338 0.8528 0.9235
No log 3.0588 52 0.8694 0.5312 0.8694 0.9324
No log 3.1765 54 0.9500 0.5312 0.9500 0.9747
No log 3.2941 56 0.9084 0.5312 0.9084 0.9531
No log 3.4118 58 0.8059 0.5312 0.8059 0.8977
No log 3.5294 60 0.8138 0.6338 0.8138 0.9021
No log 3.6471 62 0.9146 0.5422 0.9146 0.9564
No log 3.7647 64 0.9550 0.5365 0.9550 0.9773
No log 3.8824 66 0.9336 0.5365 0.9336 0.9662
No log 4.0 68 0.9319 0.5625 0.9319 0.9654
No log 4.1176 70 0.8851 0.6260 0.8851 0.9408
No log 4.2353 72 0.8516 0.6182 0.8516 0.9228
No log 4.3529 74 0.8250 0.6188 0.8250 0.9083
No log 4.4706 76 0.8158 0.6690 0.8158 0.9032
No log 4.5882 78 0.8102 0.5882 0.8102 0.9001
No log 4.7059 80 0.8191 0.5882 0.8191 0.9051
No log 4.8235 82 0.8353 0.6441 0.8353 0.9139
No log 4.9412 84 0.8613 0.6213 0.8613 0.9281
No log 5.0588 86 0.9234 0.6038 0.9234 0.9610
No log 5.1765 88 0.9213 0.5714 0.9213 0.9598
No log 5.2941 90 0.8488 0.5563 0.8488 0.9213
No log 5.4118 92 0.8263 0.5563 0.8263 0.9090
No log 5.5294 94 0.8231 0.5896 0.8231 0.9073
No log 5.6471 96 0.8229 0.6213 0.8229 0.9071
No log 5.7647 98 0.8101 0.6213 0.8101 0.9000
No log 5.8824 100 0.7902 0.6732 0.7902 0.8889
No log 6.0 102 0.7975 0.6732 0.7975 0.8930
No log 6.1176 104 0.7976 0.6732 0.7976 0.8931
No log 6.2353 106 0.8341 0.6732 0.8341 0.9133
No log 6.3529 108 0.8567 0.6677 0.8567 0.9256
No log 6.4706 110 0.9204 0.6213 0.9204 0.9594
No log 6.5882 112 0.9584 0.6038 0.9584 0.9790
No log 6.7059 114 0.9535 0.6213 0.9535 0.9765
No log 6.8235 116 0.9361 0.6213 0.9361 0.9675
No log 6.9412 118 0.8850 0.6213 0.8850 0.9407
No log 7.0588 120 0.8731 0.6213 0.8731 0.9344
No log 7.1765 122 0.8714 0.6213 0.8714 0.9335
No log 7.2941 124 0.8738 0.6213 0.8738 0.9348
No log 7.4118 126 0.8868 0.6213 0.8868 0.9417
No log 7.5294 128 0.9237 0.6213 0.9237 0.9611
No log 7.6471 130 0.9781 0.5714 0.9781 0.9890
No log 7.7647 132 0.9926 0.5686 0.9926 0.9963
No log 7.8824 134 0.9841 0.5686 0.9841 0.9920
No log 8.0 136 0.9469 0.5896 0.9469 0.9731
No log 8.1176 138 0.9149 0.5896 0.9149 0.9565
No log 8.2353 140 0.8707 0.6677 0.8707 0.9331
No log 8.3529 142 0.8480 0.7178 0.8480 0.9209
No log 8.4706 144 0.8500 0.6677 0.8500 0.9219
No log 8.5882 146 0.8616 0.6677 0.8616 0.9282
No log 8.7059 148 0.8742 0.6677 0.8742 0.9350
No log 8.8235 150 0.8966 0.5896 0.8966 0.9469
No log 8.9412 152 0.9197 0.5896 0.9197 0.9590
No log 9.0588 154 0.9430 0.5896 0.9430 0.9711
No log 9.1765 156 0.9552 0.5714 0.9552 0.9774
No log 9.2941 158 0.9605 0.5714 0.9605 0.9800
No log 9.4118 160 0.9609 0.5714 0.9609 0.9803
No log 9.5294 162 0.9624 0.5714 0.9624 0.9810
No log 9.6471 164 0.9603 0.5896 0.9603 0.9799
No log 9.7647 166 0.9534 0.5896 0.9534 0.9764
No log 9.8824 168 0.9476 0.5896 0.9476 0.9735
No log 10.0 170 0.9449 0.5896 0.9449 0.9721

Framework versions

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