Model save

README.md

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+---
+library_name: transformers
+base_model: Hartunka/distilbert_rand_100_v2
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: distilbert_rand_100_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_rand_100_v2_qqp
+
+This model is a fine-tuned version of [Hartunka/distilbert_rand_100_v2](https://huggingface.co/Hartunka/distilbert_rand_100_v2) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5895
+- Accuracy: 0.8349
+- F1: 0.7759
+- Combined Score: 0.8054
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
+| 0.4782        | 1.0   | 1422 | 0.4347          | 0.7898   | 0.6734 | 0.7316         |
+| 0.37          | 2.0   | 2844 | 0.3900          | 0.8204   | 0.7576 | 0.7890         |
+| 0.2974        | 3.0   | 4266 | 0.4048          | 0.8245   | 0.7686 | 0.7965         |
+| 0.2389        | 4.0   | 5688 | 0.4423          | 0.8311   | 0.7571 | 0.7941         |
+| 0.1926        | 5.0   | 7110 | 0.4479          | 0.8335   | 0.7663 | 0.7999         |
+| 0.1563        | 6.0   | 8532 | 0.5163          | 0.8347   | 0.7779 | 0.8063         |
+| 0.1291        | 7.0   | 9954 | 0.5895          | 0.8349   | 0.7759 | 0.8054         |
+
+
+### Framework versions
+
+- Transformers 4.50.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.21.1

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