Model save

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: google/bert_uncased_L-4_H-512_A-8
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: bert_uncased_L-4_H-512_A-8_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-512_A-8_qqp
+
+This model is a fine-tuned version of [google/bert_uncased_L-4_H-512_A-8](https://huggingface.co/google/bert_uncased_L-4_H-512_A-8) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3568
+- Accuracy: 0.8931
+- F1: 0.8604
+- Combined Score: 0.8768
+
+## 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 |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
+| 0.3551        | 1.0   | 1422  | 0.2993          | 0.8693   | 0.8179 | 0.8436         |
+| 0.2662        | 2.0   | 2844  | 0.2663          | 0.8842   | 0.8492 | 0.8667         |
+| 0.217         | 3.0   | 4266  | 0.2574          | 0.8914   | 0.8539 | 0.8727         |
+| 0.179         | 4.0   | 5688  | 0.2646          | 0.8937   | 0.8550 | 0.8744         |
+| 0.1487        | 5.0   | 7110  | 0.2920          | 0.8938   | 0.8582 | 0.8760         |
+| 0.1228        | 6.0   | 8532  | 0.2971          | 0.8936   | 0.8587 | 0.8762         |
+| 0.1042        | 7.0   | 9954  | 0.3390          | 0.8916   | 0.8577 | 0.8746         |
+| 0.0882        | 8.0   | 11376 | 0.3568          | 0.8931   | 0.8604 | 0.8768         |
+
+
+### Framework versions
+
+- Transformers 4.46.3
+- Pytorch 2.2.1+cu118
+- Datasets 2.17.0
+- Tokenizers 0.20.3

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