Model save

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: google/bert_uncased_L-2_H-256_A-4
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: bert_uncased_L-2_H-256_A-4_qnli
+  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-2_H-256_A-4_qnli
+
+This model is a fine-tuned version of [google/bert_uncased_L-2_H-256_A-4](https://huggingface.co/google/bert_uncased_L-2_H-256_A-4) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4545
+- Accuracy: 0.8098
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.516         | 1.0   | 410  | 0.4330          | 0.8056   |
+| 0.4487        | 2.0   | 820  | 0.4267          | 0.8056   |
+| 0.4136        | 3.0   | 1230 | 0.3967          | 0.8228   |
+| 0.3815        | 4.0   | 1640 | 0.4232          | 0.8116   |
+| 0.3524        | 5.0   | 2050 | 0.4196          | 0.8170   |
+| 0.3243        | 6.0   | 2460 | 0.4250          | 0.8184   |
+| 0.2993        | 7.0   | 2870 | 0.4353          | 0.8146   |
+| 0.276         | 8.0   | 3280 | 0.4545          | 0.8098   |
+
+
+### Framework versions
+
+- Transformers 4.46.3
+- Pytorch 2.2.1+cu118
+- Datasets 2.17.0
+- Tokenizers 0.20.3

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