Model save

README.md

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+---
+library_name: transformers
+base_model: Hartunka/distilbert_rand_50_v1
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: distilbert_rand_50_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_50_v1_mrpc
+
+This model is a fine-tuned version of [Hartunka/distilbert_rand_50_v1](https://huggingface.co/Hartunka/distilbert_rand_50_v1) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.2743
+- Accuracy: 0.6593
+- F1: 0.7440
+- Combined Score: 0.7017
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
+| 0.6355        | 1.0   | 15   | 0.6204          | 0.6887   | 0.7894 | 0.7391         |
+| 0.5874        | 2.0   | 30   | 0.5905          | 0.6961   | 0.8050 | 0.7506         |
+| 0.5207        | 3.0   | 45   | 0.6095          | 0.6985   | 0.7960 | 0.7473         |
+| 0.4109        | 4.0   | 60   | 0.7317          | 0.6618   | 0.75   | 0.7059         |
+| 0.2525        | 5.0   | 75   | 0.9530          | 0.6740   | 0.7542 | 0.7141         |
+| 0.1571        | 6.0   | 90   | 1.0934          | 0.6593   | 0.7477 | 0.7035         |
+| 0.1027        | 7.0   | 105  | 1.2743          | 0.6593   | 0.7440 | 0.7017         |
+
+
+### Framework versions
+
+- Transformers 4.50.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.21.1

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