Model save

README.md

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+---
+library_name: transformers
+base_model: Hartunka/bert_base_rand_5_v2
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: bert_base_rand_5_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_5_v2_qqp
+
+This model is a fine-tuned version of [Hartunka/bert_base_rand_5_v2](https://huggingface.co/Hartunka/bert_base_rand_5_v2) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5409
+- Accuracy: 0.8411
+- F1: 0.7835
+- Combined Score: 0.8123
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
+| 0.4731        | 1.0   | 1422 | 0.4262          | 0.7942   | 0.6965 | 0.7453         |
+| 0.3673        | 2.0   | 2844 | 0.3907          | 0.8174   | 0.7595 | 0.7885         |
+| 0.2918        | 3.0   | 4266 | 0.4051          | 0.8279   | 0.7746 | 0.8013         |
+| 0.2294        | 4.0   | 5688 | 0.4142          | 0.8363   | 0.7705 | 0.8034         |
+| 0.1819        | 5.0   | 7110 | 0.4686          | 0.8400   | 0.7795 | 0.8097         |
+| 0.146         | 6.0   | 8532 | 0.5030          | 0.8407   | 0.7827 | 0.8117         |
+| 0.1182        | 7.0   | 9954 | 0.5409          | 0.8411   | 0.7835 | 0.8123         |
+
+
+### Framework versions
+
+- Transformers 4.50.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.21.1

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