Model save

README.md

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+---
+library_name: transformers
+base_model: Hartunka/bert_base_km_10_v1
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: bert_base_km_10_v1_mrpc
+  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_10_v1_mrpc
+
+This model is a fine-tuned version of [Hartunka/bert_base_km_10_v1](https://huggingface.co/Hartunka/bert_base_km_10_v1) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.3684
+- Accuracy: 0.6495
+- F1: 0.7478
+- Combined Score: 0.6987
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
+| 0.6351        | 1.0   | 15   | 0.6032          | 0.7157   | 0.8123 | 0.7640         |
+| 0.5595        | 2.0   | 30   | 0.5816          | 0.7181   | 0.8177 | 0.7679         |
+| 0.4644        | 3.0   | 45   | 0.6316          | 0.6912   | 0.7812 | 0.7362         |
+| 0.3359        | 4.0   | 60   | 0.7270          | 0.6618   | 0.7612 | 0.7115         |
+| 0.1929        | 5.0   | 75   | 0.9278          | 0.6520   | 0.7341 | 0.6930         |
+| 0.0954        | 6.0   | 90   | 1.1869          | 0.6520   | 0.7526 | 0.7023         |
+| 0.0598        | 7.0   | 105  | 1.3684          | 0.6495   | 0.7478 | 0.6987         |
+
+
+### Framework versions
+
+- Transformers 4.50.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.21.1

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