Model save

README.md

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+---
+library_name: transformers
+base_model: Hartunka/distilbert_rand_10_v1
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: distilbert_rand_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. -->
+
+# distilbert_rand_10_v1_mrpc
+
+This model is a fine-tuned version of [Hartunka/distilbert_rand_10_v1](https://huggingface.co/Hartunka/distilbert_rand_10_v1) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.4431
+- Accuracy: 0.6544
+- F1: 0.7556
+- Combined Score: 0.7050
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
+| 0.6309        | 1.0   | 15   | 0.5976          | 0.6936   | 0.8013 | 0.7474         |
+| 0.5756        | 2.0   | 30   | 0.5884          | 0.6667   | 0.7748 | 0.7208         |
+| 0.507         | 3.0   | 45   | 0.6164          | 0.6985   | 0.7967 | 0.7476         |
+| 0.4021        | 4.0   | 60   | 0.7436          | 0.6838   | 0.7733 | 0.7286         |
+| 0.2627        | 5.0   | 75   | 0.9784          | 0.6127   | 0.7008 | 0.6568         |
+| 0.1522        | 6.0   | 90   | 1.2598          | 0.6397   | 0.7252 | 0.6825         |
+| 0.0925        | 7.0   | 105  | 1.4431          | 0.6544   | 0.7556 | 0.7050         |
+
+
+### Framework versions
+
+- Transformers 4.50.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.21.1

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