Model save

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: TomasFAV/BERTInvoiceCzechV01
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: BERTInvoiceCzechV013
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# BERTInvoiceCzechV013
+
+This model is a fine-tuned version of [TomasFAV/BERTInvoiceCzechV01](https://huggingface.co/TomasFAV/BERTInvoiceCzechV01) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0691
+- Precision: 0.8399
+- Recall: 0.8819
+- F1: 0.8604
+- Accuracy: 0.9810
+
+## 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: 1e-05
+- train_batch_size: 16
+- eval_batch_size: 2
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 0.1
+- num_epochs: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 20   | 0.1182          | 0.7538    | 0.7538 | 0.7538 | 0.9674   |
+| No log        | 2.0   | 40   | 0.1039          | 0.7627    | 0.8237 | 0.7920 | 0.9716   |
+| No log        | 3.0   | 60   | 0.0867          | 0.7909    | 0.8505 | 0.8196 | 0.9756   |
+| No log        | 4.0   | 80   | 0.0769          | 0.8134    | 0.8839 | 0.8472 | 0.9785   |
+| No log        | 5.0   | 100  | 0.0728          | 0.8298    | 0.8858 | 0.8569 | 0.9797   |
+| No log        | 6.0   | 120  | 0.0746          | 0.8138    | 0.8812 | 0.8462 | 0.9785   |
+| No log        | 7.0   | 140  | 0.0753          | 0.8093    | 0.8897 | 0.8476 | 0.9777   |
+| No log        | 8.0   | 160  | 0.0703          | 0.8325    | 0.8858 | 0.8583 | 0.9802   |
+| No log        | 9.0   | 180  | 0.0716          | 0.8307    | 0.8839 | 0.8564 | 0.9803   |
+| No log        | 10.0  | 200  | 0.0691          | 0.8399    | 0.8819 | 0.8604 | 0.9810   |
+
+
+### Framework versions
+
+- Transformers 5.0.0
+- Pytorch 2.10.0+cu128
+- Datasets 4.0.0
+- Tokenizers 0.22.2

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