Model save

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: google/bert_uncased_L-4_H-128_A-2
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: bert_uncased_L-4_H-128_A-2_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_uncased_L-4_H-128_A-2_mnli
+
+This model is a fine-tuned version of [google/bert_uncased_L-4_H-128_A-2](https://huggingface.co/google/bert_uncased_L-4_H-128_A-2) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6699
+- Accuracy: 0.7343
+
+## 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 |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 0.8752        | 1.0   | 1534  | 0.7743          | 0.6558   |
+| 0.7714        | 2.0   | 3068  | 0.7263          | 0.6857   |
+| 0.7255        | 3.0   | 4602  | 0.6946          | 0.7020   |
+| 0.6927        | 4.0   | 6136  | 0.6789          | 0.7087   |
+| 0.6662        | 5.0   | 7670  | 0.6657          | 0.7205   |
+| 0.6441        | 6.0   | 9204  | 0.6691          | 0.7229   |
+| 0.625         | 7.0   | 10738 | 0.6622          | 0.7258   |
+| 0.607         | 8.0   | 12272 | 0.6531          | 0.7314   |
+| 0.5894        | 9.0   | 13806 | 0.6613          | 0.7308   |
+| 0.5754        | 10.0  | 15340 | 0.6591          | 0.7293   |
+| 0.5615        | 11.0  | 16874 | 0.6635          | 0.7287   |
+| 0.5477        | 12.0  | 18408 | 0.6701          | 0.7344   |
+| 0.5343        | 13.0  | 19942 | 0.6699          | 0.7343   |
+
+
+### Framework versions
+
+- Transformers 4.46.3
+- Pytorch 2.2.1+cu118
+- Datasets 2.17.0
+- Tokenizers 0.20.3

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