Model save

README.md

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+---
+library_name: transformers
+base_model: Hartunka/bert_base_rand_50_v1
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: bert_base_rand_50_v1_mnli
+  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. -->
+
+# bert_base_rand_50_v1_mnli
+
+This model is a fine-tuned version of [Hartunka/bert_base_rand_50_v1](https://huggingface.co/Hartunka/bert_base_rand_50_v1) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.0435
+- Accuracy: 0.6624
+
+## 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 |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 0.9773        | 1.0   | 1534  | 0.9061          | 0.5769   |
+| 0.868         | 2.0   | 3068  | 0.8350          | 0.6298   |
+| 0.7722        | 3.0   | 4602  | 0.7925          | 0.6542   |
+| 0.6949        | 4.0   | 6136  | 0.7740          | 0.6617   |
+| 0.626         | 5.0   | 7670  | 0.8050          | 0.6711   |
+| 0.5557        | 6.0   | 9204  | 0.8318          | 0.6773   |
+| 0.484         | 7.0   | 10738 | 0.8868          | 0.6729   |
+| 0.4158        | 8.0   | 12272 | 0.9603          | 0.6697   |
+| 0.3534        | 9.0   | 13806 | 1.0435          | 0.6624   |
+
+
+### Framework versions
+
+- Transformers 4.50.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.21.1

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