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_padding40model
+  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: 0.9473684210526315
+---
+
+<!-- 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_padding40model
+
+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: 0.5661
+- Accuracy: 0.9474
+
+## 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 |
+|:-------------:|:-----:|:------:|:---------------:|:--------:|
+| 0.1785        | 1.0   | 7500   | 0.1884          | 0.9421   |
+| 0.1379        | 2.0   | 15000  | 0.1990          | 0.9478   |
+| 0.1127        | 3.0   | 22500  | 0.2389          | 0.9408   |
+| 0.0846        | 4.0   | 30000  | 0.2528          | 0.9492   |
+| 0.0581        | 5.0   | 37500  | 0.3041          | 0.9436   |
+| 0.0456        | 6.0   | 45000  | 0.3415          | 0.9468   |
+| 0.0411        | 7.0   | 52500  | 0.4081          | 0.9430   |
+| 0.0239        | 8.0   | 60000  | 0.4415          | 0.9433   |
+| 0.0202        | 9.0   | 67500  | 0.4380          | 0.9404   |
+| 0.0126        | 10.0  | 75000  | 0.4637          | 0.9425   |
+| 0.0175        | 11.0  | 82500  | 0.4485          | 0.9455   |
+| 0.0126        | 12.0  | 90000  | 0.4761          | 0.9449   |
+| 0.0046        | 13.0  | 97500  | 0.5009          | 0.9455   |
+| 0.0038        | 14.0  | 105000 | 0.4784          | 0.9482   |
+| 0.0035        | 15.0  | 112500 | 0.5282          | 0.9451   |
+| 0.0046        | 16.0  | 120000 | 0.5256          | 0.9464   |
+| 0.0026        | 17.0  | 127500 | 0.5081          | 0.9501   |
+| 0.0008        | 18.0  | 135000 | 0.5543          | 0.9467   |
+| 0.0002        | 19.0  | 142500 | 0.5448          | 0.9488   |
+| 0.0016        | 20.0  | 150000 | 0.5661          | 0.9474   |
+
+
+### Framework versions
+
+- Transformers 4.33.2
+- Pytorch 2.0.1+cu117
+- Datasets 2.14.5
+- Tokenizers 0.13.3

pytorch_model.bin

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