Model save

README.md

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+---
+library_name: transformers
+base_model: Hartunka/bert_base_rand_10_v2
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: bert_base_rand_10_v2_qqp
+  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_base_rand_10_v2_qqp
+
+This model is a fine-tuned version of [Hartunka/bert_base_rand_10_v2](https://huggingface.co/Hartunka/bert_base_rand_10_v2) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6163
+- Accuracy: 0.8422
+- F1: 0.7848
+- Combined Score: 0.8135
+
+## 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: 256
+- eval_batch_size: 256
+- seed: 10
+- optimizer: Use 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: 50
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Combined Score |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
+| 0.4757        | 1.0   | 1422 | 0.4355          | 0.7913   | 0.6756 | 0.7335         |
+| 0.3701        | 2.0   | 2844 | 0.3871          | 0.8203   | 0.7589 | 0.7896         |
+| 0.294         | 3.0   | 4266 | 0.3957          | 0.8242   | 0.7747 | 0.7995         |
+| 0.2331        | 4.0   | 5688 | 0.4476          | 0.8343   | 0.7689 | 0.8016         |
+| 0.1845        | 5.0   | 7110 | 0.4730          | 0.8396   | 0.7799 | 0.8098         |
+| 0.1496        | 6.0   | 8532 | 0.4950          | 0.8421   | 0.7814 | 0.8118         |
+| 0.1215        | 7.0   | 9954 | 0.6163          | 0.8422   | 0.7848 | 0.8135         |
+
+
+### Framework versions
+
+- Transformers 4.50.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.21.1

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