Model save

README.md

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+---
+library_name: transformers
+base_model: Hartunka/bert_base_rand_10_v1
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: bert_base_rand_10_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_10_v1_qqp
+
+This model is a fine-tuned version of [Hartunka/bert_base_rand_10_v1](https://huggingface.co/Hartunka/bert_base_rand_10_v1) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5849
+- Accuracy: 0.8363
+- F1: 0.7872
+- Combined Score: 0.8117
+
+## 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  | 0.4247          | 0.7962   | 0.7029 | 0.7495         |
+| 0.3697        | 2.0   | 2844  | 0.3917          | 0.8153   | 0.7582 | 0.7868         |
+| 0.2939        | 3.0   | 4266  | 0.3889          | 0.8288   | 0.7734 | 0.8011         |
+| 0.2329        | 4.0   | 5688  | 0.4264          | 0.8376   | 0.7722 | 0.8049         |
+| 0.1847        | 5.0   | 7110  | 0.4509          | 0.8404   | 0.7807 | 0.8106         |
+| 0.1492        | 6.0   | 8532  | 0.4776          | 0.8399   | 0.7801 | 0.8100         |
+| 0.122         | 7.0   | 9954  | 0.5778          | 0.8429   | 0.7829 | 0.8129         |
+| 0.1009        | 8.0   | 11376 | 0.5849          | 0.8363   | 0.7872 | 0.8117         |
+
+
+### Framework versions
+
+- Transformers 4.50.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.21.1

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