Model save

README.md

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+---
+library_name: transformers
+base_model: Hartunka/distilbert_km_10_v2
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: distilbert_km_10_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. -->
+
+# distilbert_km_10_v2_qqp
+
+This model is a fine-tuned version of [Hartunka/distilbert_km_10_v2](https://huggingface.co/Hartunka/distilbert_km_10_v2) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5898
+- Accuracy: 0.8289
+- F1: 0.7747
+- Combined Score: 0.8018
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
+| 0.4781        | 1.0   | 1422 | 0.4353          | 0.7922   | 0.6916 | 0.7419         |
+| 0.3737        | 2.0   | 2844 | 0.4022          | 0.8152   | 0.7424 | 0.7788         |
+| 0.2966        | 3.0   | 4266 | 0.4022          | 0.8235   | 0.7638 | 0.7937         |
+| 0.2309        | 4.0   | 5688 | 0.4382          | 0.8306   | 0.7563 | 0.7935         |
+| 0.1801        | 5.0   | 7110 | 0.4994          | 0.8319   | 0.7657 | 0.7988         |
+| 0.1423        | 6.0   | 8532 | 0.5064          | 0.8275   | 0.7721 | 0.7998         |
+| 0.1143        | 7.0   | 9954 | 0.5898          | 0.8289   | 0.7747 | 0.8018         |
+
+
+### Framework versions
+
+- Transformers 4.50.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.21.1

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