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fine_tuned_ancient_semitic_BERT

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metadata
base_model: mehdie/ancient_semitic_bert
tags:
  - generated_from_trainer
metrics:
  - f1
  - precision
  - recall
model-index:
  - name: fine_tuned_ancient_semitic_BERT
    results: []

fine_tuned_ancient_semitic_BERT

This model is a fine-tuned version of mehdie/ancient_semitic_bert on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3771
  • F1: 0.5652
  • F5: 0.5748
  • Precision: 0.5417
  • Recall: 0.5909

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: 128
  • eval_batch_size: 128
  • seed: 42
  • distributed_type: multi-GPU
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 25
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss F1 F5 Precision Recall
No log 1.0 17 0.3386 0.0 0.0 0.0 0.0
No log 2.0 34 0.3252 0.0 0.0 0.0 0.0
No log 3.0 51 0.3188 0.0 0.0 0.0 0.0
No log 4.0 68 0.3410 0.0 0.0 0.0 0.0
No log 5.0 85 0.3069 0.1379 0.1080 0.5 0.08
No log 6.0 102 0.3209 0.1379 0.1080 0.5 0.08
No log 7.0 119 0.3432 0.2222 0.2132 0.25 0.2
No log 8.0 136 0.3606 0.2727 0.2592 0.3158 0.24
No log 9.0 153 0.3319 0.2927 0.2700 0.375 0.24
No log 10.0 170 0.3741 0.4074 0.4193 0.3793 0.44
No log 11.0 187 0.3008 0.3784 0.3336 0.5833 0.28
No log 12.0 204 0.3237 0.4231 0.4294 0.4074 0.44
No log 13.0 221 0.2848 0.5 0.4752 0.5789 0.44
No log 14.0 238 0.3058 0.52 0.52 0.52 0.52
No log 15.0 255 0.2912 0.5417 0.5332 0.5652 0.52
No log 16.0 272 0.3005 0.4681 0.4569 0.5 0.44
No log 17.0 289 0.3122 0.5556 0.5717 0.5172 0.6
No log 18.0 306 0.3670 0.5667 0.6052 0.4857 0.68
No log 19.0 323 0.2818 0.5926 0.6098 0.5517 0.64
No log 20.0 340 0.3012 0.5882 0.5927 0.5769 0.6
No log 21.0 357 0.3288 0.6154 0.6246 0.5926 0.64
No log 22.0 374 0.3251 0.6250 0.6152 0.6522 0.6
No log 23.0 391 0.3145 0.6250 0.6152 0.6522 0.6
No log 24.0 408 0.3128 0.68 0.68 0.68 0.68
No log 25.0 425 0.3190 0.6538 0.6636 0.6296 0.68

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.3.0a0+ebedce2
  • Datasets 2.17.1
  • Tokenizers 0.15.2