Model save

README.md

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+---
+library_name: transformers
+base_model: Hartunka/bert_base_rand_5_v1
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: bert_base_rand_5_v1_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_5_v1_qqp
+
+This model is a fine-tuned version of [Hartunka/bert_base_rand_5_v1](https://huggingface.co/Hartunka/bert_base_rand_5_v1) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5547
+- Accuracy: 0.8408
+- F1: 0.7851
+- Combined Score: 0.8129
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
+| 0.4751        | 1.0   | 1422 | 0.4341          | 0.7920   | 0.6797 | 0.7359         |
+| 0.3657        | 2.0   | 2844 | 0.3895          | 0.8175   | 0.7661 | 0.7918         |
+| 0.2876        | 3.0   | 4266 | 0.4063          | 0.8242   | 0.7753 | 0.7998         |
+| 0.2268        | 4.0   | 5688 | 0.4114          | 0.8354   | 0.7774 | 0.8064         |
+| 0.1778        | 5.0   | 7110 | 0.4330          | 0.8397   | 0.7851 | 0.8124         |
+| 0.1429        | 6.0   | 8532 | 0.5096          | 0.8441   | 0.7814 | 0.8128         |
+| 0.1145        | 7.0   | 9954 | 0.5547          | 0.8408   | 0.7851 | 0.8129         |
+
+
+### Framework versions
+
+- Transformers 4.50.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.21.1

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