Model save

README.md

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+---
+library_name: transformers
+base_model: Hartunka/bert_base_km_50_v2
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: bert_base_km_50_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_50_v2_qqp
+
+This model is a fine-tuned version of [Hartunka/bert_base_km_50_v2](https://huggingface.co/Hartunka/bert_base_km_50_v2) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5793
+- Accuracy: 0.8286
+- F1: 0.7794
+- Combined Score: 0.8040
+
+## 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 |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
+| 0.4831        | 1.0   | 1422  | 0.4464          | 0.7857   | 0.6639 | 0.7248         |
+| 0.3789        | 2.0   | 2844  | 0.3969          | 0.8142   | 0.7440 | 0.7791         |
+| 0.3007        | 3.0   | 4266  | 0.3899          | 0.8244   | 0.7620 | 0.7932         |
+| 0.2341        | 4.0   | 5688  | 0.4301          | 0.8297   | 0.7578 | 0.7937         |
+| 0.18          | 5.0   | 7110  | 0.4499          | 0.8295   | 0.7779 | 0.8037         |
+| 0.1381        | 6.0   | 8532  | 0.5405          | 0.8346   | 0.7790 | 0.8068         |
+| 0.1072        | 7.0   | 9954  | 0.5882          | 0.8326   | 0.7779 | 0.8052         |
+| 0.0866        | 8.0   | 11376 | 0.5793          | 0.8286   | 0.7794 | 0.8040         |
+
+
+### Framework versions
+
+- Transformers 4.50.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.21.1

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