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--- |
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base_model: mehdie/ancient_semitic_bert |
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tags: |
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- generated_from_trainer |
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metrics: |
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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: fine_tuned_ancient_semitic_BERT |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# fine_tuned_ancient_semitic_BERT |
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This model is a fine-tuned version of [mehdie/ancient_semitic_bert](https://huggingface.co/mehdie/ancient_semitic_bert) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3771 |
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- F1: 0.5652 |
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- F5: 0.5748 |
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- Precision: 0.5417 |
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- Recall: 0.5909 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 128 |
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- eval_batch_size: 128 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 25 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | F5 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:---------:|:------:| |
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| No log | 1.0 | 17 | 0.3386 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| No log | 2.0 | 34 | 0.3252 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| No log | 3.0 | 51 | 0.3188 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| No log | 4.0 | 68 | 0.3410 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| No log | 5.0 | 85 | 0.3069 | 0.1379 | 0.1080 | 0.5 | 0.08 | |
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| No log | 6.0 | 102 | 0.3209 | 0.1379 | 0.1080 | 0.5 | 0.08 | |
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| No log | 7.0 | 119 | 0.3432 | 0.2222 | 0.2132 | 0.25 | 0.2 | |
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| No log | 8.0 | 136 | 0.3606 | 0.2727 | 0.2592 | 0.3158 | 0.24 | |
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| No log | 9.0 | 153 | 0.3319 | 0.2927 | 0.2700 | 0.375 | 0.24 | |
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| No log | 10.0 | 170 | 0.3741 | 0.4074 | 0.4193 | 0.3793 | 0.44 | |
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| No log | 11.0 | 187 | 0.3008 | 0.3784 | 0.3336 | 0.5833 | 0.28 | |
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| No log | 12.0 | 204 | 0.3237 | 0.4231 | 0.4294 | 0.4074 | 0.44 | |
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| No log | 13.0 | 221 | 0.2848 | 0.5 | 0.4752 | 0.5789 | 0.44 | |
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| No log | 14.0 | 238 | 0.3058 | 0.52 | 0.52 | 0.52 | 0.52 | |
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| No log | 15.0 | 255 | 0.2912 | 0.5417 | 0.5332 | 0.5652 | 0.52 | |
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| No log | 16.0 | 272 | 0.3005 | 0.4681 | 0.4569 | 0.5 | 0.44 | |
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| No log | 17.0 | 289 | 0.3122 | 0.5556 | 0.5717 | 0.5172 | 0.6 | |
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| No log | 18.0 | 306 | 0.3670 | 0.5667 | 0.6052 | 0.4857 | 0.68 | |
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| No log | 19.0 | 323 | 0.2818 | 0.5926 | 0.6098 | 0.5517 | 0.64 | |
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| No log | 20.0 | 340 | 0.3012 | 0.5882 | 0.5927 | 0.5769 | 0.6 | |
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| No log | 21.0 | 357 | 0.3288 | 0.6154 | 0.6246 | 0.5926 | 0.64 | |
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| No log | 22.0 | 374 | 0.3251 | 0.6250 | 0.6152 | 0.6522 | 0.6 | |
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| No log | 23.0 | 391 | 0.3145 | 0.6250 | 0.6152 | 0.6522 | 0.6 | |
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| No log | 24.0 | 408 | 0.3128 | 0.68 | 0.68 | 0.68 | 0.68 | |
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| No log | 25.0 | 425 | 0.3190 | 0.6538 | 0.6636 | 0.6296 | 0.68 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.3.0a0+ebedce2 |
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- Datasets 2.17.1 |
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- Tokenizers 0.15.2 |
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