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POEMS-CAMELBERT-CA-RUN4-20-fullData

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POEMS-CAMELBERT-CA-RUN4-20-fullData / README.md
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metadata
license: apache-2.0
base_model: CAMeL-Lab/bert-base-arabic-camelbert-ca
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: POEMS-CAMELBERT-CA-RUN4-20-fullData
    results: []

POEMS-CAMELBERT-CA-RUN4-20-fullData

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: 3.1172
  • Accuracy: 0.6210
  • F1: 0.6210
  • Precision: 0.6210
  • Recall: 0.6210

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: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy F1 Precision Recall
1.1804 1.0 568 1.1103 0.5066 0.5066 0.5066 0.5066
0.9771 2.0 1136 0.9937 0.5847 0.5847 0.5847 0.5847
0.8057 3.0 1704 1.0751 0.5882 0.5882 0.5882 0.5882
0.6404 4.0 2272 1.1029 0.6011 0.6011 0.6011 0.6011
0.4956 5.0 2840 1.1222 0.6064 0.6064 0.6064 0.6064
0.3742 6.0 3408 1.2714 0.6077 0.6077 0.6077 0.6077
0.2881 7.0 3976 1.5337 0.5931 0.5931 0.5931 0.5931
0.2153 8.0 4544 1.6150 0.5984 0.5984 0.5984 0.5984
0.1663 9.0 5112 1.7246 0.6037 0.6037 0.6037 0.6037
0.1266 10.0 5680 2.0767 0.5984 0.5984 0.5984 0.5984
0.1064 11.0 6248 2.1690 0.6161 0.6161 0.6161 0.6161
0.0895 12.0 6816 2.4732 0.6068 0.6068 0.6068 0.6068
0.0794 13.0 7384 2.4153 0.6095 0.6095 0.6095 0.6095
0.0555 14.0 7952 2.8754 0.6037 0.6037 0.6037 0.6037
0.0502 15.0 8520 2.8673 0.6121 0.6121 0.6121 0.6121
0.0383 16.0 9088 2.9805 0.6139 0.6139 0.6139 0.6139
0.0329 17.0 9656 3.0402 0.6188 0.6188 0.6188 0.6188
0.0237 18.0 10224 3.0225 0.6263 0.6263 0.6263 0.6263
0.0173 19.0 10792 3.0629 0.6206 0.6206 0.6206 0.6206
0.0169 20.0 11360 3.1172 0.6210 0.6210 0.6210 0.6210

Framework versions

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