Model save

README.md

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+---
+library_name: transformers
+base_model: Hartunka/distilbert_km_20_v1
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: distilbert_km_20_v1_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_20_v1_qqp
+
+This model is a fine-tuned version of [Hartunka/distilbert_km_20_v1](https://huggingface.co/Hartunka/distilbert_km_20_v1) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5558
+- Accuracy: 0.8324
+- F1: 0.7772
+- Combined Score: 0.8048
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
+| 0.485         | 1.0   | 1422 | 0.4343          | 0.7906   | 0.6921 | 0.7413         |
+| 0.3809        | 2.0   | 2844 | 0.3983          | 0.8152   | 0.7476 | 0.7814         |
+| 0.307         | 3.0   | 4266 | 0.3997          | 0.8230   | 0.7683 | 0.7957         |
+| 0.2452        | 4.0   | 5688 | 0.4376          | 0.8293   | 0.7561 | 0.7927         |
+| 0.1961        | 5.0   | 7110 | 0.4592          | 0.8329   | 0.7672 | 0.8001         |
+| 0.1568        | 6.0   | 8532 | 0.5182          | 0.8240   | 0.7739 | 0.7989         |
+| 0.1273        | 7.0   | 9954 | 0.5558          | 0.8324   | 0.7772 | 0.8048         |
+
+
+### Framework versions
+
+- Transformers 4.50.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.21.1

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