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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: google-bert/bert-base-multilingual-cased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: BERTInvoiceCzech |
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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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# BERTInvoiceCzech |
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This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0222 |
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- Precision: 0.9591 |
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- Recall: 0.9633 |
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- F1: 0.9612 |
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- Accuracy: 0.9929 |
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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: 1e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 20 |
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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 | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| No log | 1.0 | 42 | 1.2228 | 0.0 | 0.0 | 0.0 | 0.7831 | |
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| No log | 2.0 | 84 | 0.5729 | 0.4183 | 0.4014 | 0.4097 | 0.8535 | |
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| No log | 3.0 | 126 | 0.3043 | 0.6654 | 0.6861 | 0.6756 | 0.9155 | |
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| No log | 4.0 | 168 | 0.2019 | 0.7618 | 0.7872 | 0.7743 | 0.9406 | |
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| No log | 5.0 | 210 | 0.1278 | 0.8161 | 0.8587 | 0.8369 | 0.9627 | |
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| No log | 6.0 | 252 | 0.0823 | 0.8727 | 0.9063 | 0.8892 | 0.9762 | |
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| No log | 7.0 | 294 | 0.0599 | 0.9086 | 0.9284 | 0.9184 | 0.9824 | |
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| No log | 8.0 | 336 | 0.0451 | 0.9335 | 0.9484 | 0.9409 | 0.9864 | |
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| No log | 9.0 | 378 | 0.0373 | 0.9388 | 0.9499 | 0.9443 | 0.9877 | |
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| No log | 10.0 | 420 | 0.0323 | 0.9458 | 0.9558 | 0.9508 | 0.9897 | |
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| No log | 11.0 | 462 | 0.0283 | 0.9506 | 0.9580 | 0.9543 | 0.9914 | |
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| 0.4073 | 12.0 | 504 | 0.0277 | 0.9567 | 0.9620 | 0.9594 | 0.9920 | |
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| 0.4073 | 13.0 | 546 | 0.0243 | 0.9517 | 0.9568 | 0.9542 | 0.9916 | |
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| 0.4073 | 14.0 | 588 | 0.0256 | 0.9610 | 0.9661 | 0.9635 | 0.9928 | |
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| 0.4073 | 15.0 | 630 | 0.0245 | 0.9588 | 0.9633 | 0.9610 | 0.9927 | |
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| 0.4073 | 16.0 | 672 | 0.0231 | 0.9606 | 0.9636 | 0.9621 | 0.9930 | |
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| 0.4073 | 17.0 | 714 | 0.0239 | 0.9582 | 0.9627 | 0.9604 | 0.9925 | |
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| 0.4073 | 18.0 | 756 | 0.0221 | 0.9606 | 0.9642 | 0.9624 | 0.9931 | |
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| 0.4073 | 19.0 | 798 | 0.0222 | 0.9594 | 0.9639 | 0.9617 | 0.9930 | |
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| 0.4073 | 20.0 | 840 | 0.0222 | 0.9591 | 0.9633 | 0.9612 | 0.9929 | |
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### Framework versions |
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- Transformers 4.57.6 |
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- Pytorch 2.9.0+cu126 |
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- Datasets 4.0.0 |
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- Tokenizers 0.22.2 |
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