End of training

README.md

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+---
+license: apache-2.0
+base_model: bert-base-uncased
+tags:
+- generated_from_trainer
+datasets:
+- ag_news
+metrics:
+- accuracy
+model-index:
+- name: N_bert_agnews_padding50model
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: ag_news
+      type: ag_news
+      config: default
+      split: test
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9467105263157894
+---
+
+<!-- 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. -->
+
+# N_bert_agnews_padding50model
+
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the ag_news dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5754
+- Accuracy: 0.9467
+
+## 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: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 20
+
+### Training results
+
+| Training Loss | Epoch | Step   | Validation Loss | Accuracy |
+|:-------------:|:-----:|:------:|:---------------:|:--------:|
+| 0.1754        | 1.0   | 7500   | 0.1909          | 0.9428   |
+| 0.1362        | 2.0   | 15000  | 0.1928          | 0.9461   |
+| 0.1139        | 3.0   | 22500  | 0.2106          | 0.9461   |
+| 0.0825        | 4.0   | 30000  | 0.2544          | 0.9466   |
+| 0.0565        | 5.0   | 37500  | 0.3046          | 0.9367   |
+| 0.0372        | 6.0   | 45000  | 0.3764          | 0.9436   |
+| 0.0347        | 7.0   | 52500  | 0.3646          | 0.9425   |
+| 0.0346        | 8.0   | 60000  | 0.3826          | 0.9461   |
+| 0.0247        | 9.0   | 67500  | 0.4244          | 0.9455   |
+| 0.0113        | 10.0  | 75000  | 0.4418          | 0.9446   |
+| 0.0166        | 11.0  | 82500  | 0.4917          | 0.9462   |
+| 0.0157        | 12.0  | 90000  | 0.4662          | 0.9442   |
+| 0.0124        | 13.0  | 97500  | 0.4864          | 0.9438   |
+| 0.0055        | 14.0  | 105000 | 0.4912          | 0.9457   |
+| 0.0102        | 15.0  | 112500 | 0.5040          | 0.9446   |
+| 0.0045        | 16.0  | 120000 | 0.5200          | 0.9441   |
+| 0.0038        | 17.0  | 127500 | 0.5374          | 0.9467   |
+| 0.0012        | 18.0  | 135000 | 0.5605          | 0.9459   |
+| 0.0005        | 19.0  | 142500 | 0.5809          | 0.9455   |
+| 0.0003        | 20.0  | 150000 | 0.5754          | 0.9467   |
+
+
+### Framework versions
+
+- Transformers 4.33.2
+- Pytorch 2.0.1+cu117
+- Datasets 2.14.5
+- Tokenizers 0.13.3

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