Model save

README.md

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+---
+library_name: transformers
+base_model: Hartunka/distilbert_km_50_v2
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: distilbert_km_50_v2_qnli
+  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_50_v2_qnli
+
+This model is a fine-tuned version of [Hartunka/distilbert_km_50_v2](https://huggingface.co/Hartunka/distilbert_km_50_v2) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.2523
+- Accuracy: 0.6121
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.6688        | 1.0   | 410  | 0.6536          | 0.6081   |
+| 0.6354        | 2.0   | 820  | 0.6507          | 0.6150   |
+| 0.5863        | 3.0   | 1230 | 0.6440          | 0.6326   |
+| 0.5027        | 4.0   | 1640 | 0.7138          | 0.6231   |
+| 0.4002        | 5.0   | 2050 | 0.8596          | 0.6209   |
+| 0.3023        | 6.0   | 2460 | 1.0442          | 0.6161   |
+| 0.2266        | 7.0   | 2870 | 1.2265          | 0.6110   |
+| 0.1741        | 8.0   | 3280 | 1.2523          | 0.6121   |
+
+
+### Framework versions
+
+- Transformers 4.50.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.21.1

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