Model save

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: google/bert_uncased_L-4_H-256_A-4
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: bert_uncased_L-4_H-256_A-4_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. -->
+
+# bert_uncased_L-4_H-256_A-4_qqp
+
+This model is a fine-tuned version of [google/bert_uncased_L-4_H-256_A-4](https://huggingface.co/google/bert_uncased_L-4_H-256_A-4) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3125
+- Accuracy: 0.8863
+- F1: 0.8526
+- Combined Score: 0.8694
+
+## 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 |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
+| 0.3985        | 1.0   | 1422  | 0.3341          | 0.8486   | 0.7966 | 0.8226         |
+| 0.3199        | 2.0   | 2844  | 0.3058          | 0.8636   | 0.8245 | 0.8440         |
+| 0.2819        | 3.0   | 4266  | 0.2883          | 0.8732   | 0.8341 | 0.8536         |
+| 0.2525        | 4.0   | 5688  | 0.2840          | 0.8775   | 0.8327 | 0.8551         |
+| 0.2304        | 5.0   | 7110  | 0.2858          | 0.8808   | 0.8448 | 0.8628         |
+| 0.2094        | 6.0   | 8532  | 0.2877          | 0.8817   | 0.8450 | 0.8633         |
+| 0.1912        | 7.0   | 9954  | 0.2909          | 0.8823   | 0.8462 | 0.8642         |
+| 0.1749        | 8.0   | 11376 | 0.2944          | 0.8856   | 0.8512 | 0.8684         |
+| 0.1604        | 9.0   | 12798 | 0.3125          | 0.8863   | 0.8526 | 0.8694         |
+
+
+### Framework versions
+
+- Transformers 4.46.3
+- Pytorch 2.2.1+cu118
+- Datasets 2.17.0
+- Tokenizers 0.20.3

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