Model save

README.md

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+---
+library_name: transformers
+base_model: Hartunka/bert_base_km_100_v1
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: bert_base_km_100_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_km_100_v1_qqp
+
+This model is a fine-tuned version of [Hartunka/bert_base_km_100_v1](https://huggingface.co/Hartunka/bert_base_km_100_v1) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6060
+- Accuracy: 0.8328
+- F1: 0.7638
+- Combined Score: 0.7983
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
+| 0.483         | 1.0   | 1422 | 0.4432          | 0.7904   | 0.6882 | 0.7393         |
+| 0.3749        | 2.0   | 2844 | 0.3926          | 0.8175   | 0.7473 | 0.7824         |
+| 0.2912        | 3.0   | 4266 | 0.3976          | 0.8258   | 0.7647 | 0.7953         |
+| 0.2189        | 4.0   | 5688 | 0.4471          | 0.8304   | 0.7616 | 0.7960         |
+| 0.1641        | 5.0   | 7110 | 0.4702          | 0.8310   | 0.7686 | 0.7998         |
+| 0.126         | 6.0   | 8532 | 0.5648          | 0.8332   | 0.7700 | 0.8016         |
+| 0.1003        | 7.0   | 9954 | 0.6060          | 0.8328   | 0.7638 | 0.7983         |
+
+
+### Framework versions
+
+- Transformers 4.50.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.21.1

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