End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: anferico/bert-for-patents
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: bert-for-patents-finetuned_ls-sys2
+  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. -->
+
+# bert-for-patents-finetuned_ls-sys2
+
+This model is a fine-tuned version of [anferico/bert-for-patents](https://huggingface.co/anferico/bert-for-patents) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0529
+- Accuracy: 0.981
+- Auc: 0.998
+- F1: 0.958
+- Precision: 0.962
+- Recall: 0.955
+
+## 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: 2e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Auc   | F1    | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----:|:-----:|:---------:|:------:|
+| 0.3254        | 1.0   | 993  | 0.1486          | 0.947    | 0.987 | 0.88  | 0.922     | 0.841  |
+| 0.1237        | 2.0   | 1986 | 0.0887          | 0.969    | 0.995 | 0.931 | 0.945     | 0.918  |
+| 0.0928        | 3.0   | 2979 | 0.0718          | 0.973    | 0.996 | 0.94  | 0.962     | 0.919  |
+| 0.0811        | 4.0   | 3972 | 0.0635          | 0.977    | 0.997 | 0.949 | 0.96      | 0.939  |
+| 0.0748        | 5.0   | 4965 | 0.0596          | 0.979    | 0.997 | 0.953 | 0.955     | 0.952  |
+| 0.0695        | 6.0   | 5958 | 0.0563          | 0.98     | 0.997 | 0.955 | 0.962     | 0.949  |
+| 0.0682        | 7.0   | 6951 | 0.0552          | 0.98     | 0.997 | 0.957 | 0.958     | 0.956  |
+| 0.0664        | 8.0   | 7944 | 0.0537          | 0.981    | 0.997 | 0.958 | 0.961     | 0.954  |
+| 0.0642        | 9.0   | 8937 | 0.0530          | 0.981    | 0.998 | 0.958 | 0.962     | 0.954  |
+| 0.0647        | 10.0  | 9930 | 0.0529          | 0.981    | 0.998 | 0.958 | 0.962     | 0.955  |
+
+
+### Framework versions
+
+- Transformers 4.49.0
+- Pytorch 2.6.0+cu124
+- Datasets 3.4.1
+- Tokenizers 0.21.1

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