Model save

README.md

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+---
+library_name: transformers
+base_model: Hartunka/bert_base_km_100_v2
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: bert_base_km_100_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_km_100_v2_qqp
+
+This model is a fine-tuned version of [Hartunka/bert_base_km_100_v2](https://huggingface.co/Hartunka/bert_base_km_100_v2) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6412
+- Accuracy: 0.8315
+- F1: 0.7762
+- Combined Score: 0.8038
+
+## 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 |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
+| 0.4851        | 1.0   | 1422  | 0.4543          | 0.7842   | 0.6573 | 0.7207         |
+| 0.3784        | 2.0   | 2844  | 0.4032          | 0.8116   | 0.7570 | 0.7843         |
+| 0.2978        | 3.0   | 4266  | 0.4003          | 0.8197   | 0.7688 | 0.7942         |
+| 0.2292        | 4.0   | 5688  | 0.4379          | 0.8305   | 0.7631 | 0.7968         |
+| 0.1741        | 5.0   | 7110  | 0.4736          | 0.8309   | 0.7750 | 0.8030         |
+| 0.1338        | 6.0   | 8532  | 0.5308          | 0.8355   | 0.7702 | 0.8029         |
+| 0.1055        | 7.0   | 9954  | 0.5860          | 0.8292   | 0.7774 | 0.8033         |
+| 0.0843        | 8.0   | 11376 | 0.6412          | 0.8315   | 0.7762 | 0.8038         |
+
+
+### Framework versions
+
+- Transformers 4.50.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.21.1

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