End of training

README.md

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+---
+license: apache-2.0
+base_model: google-bert/bert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: dnd_en
+  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. -->
+
+# dnd_en
+
+This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3371
+- Accuracy: 0.8947
+
+## 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-06
+- 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: 12
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 15   | 0.4992          | 0.8421   |
+| No log        | 2.0   | 30   | 0.4656          | 0.8772   |
+| No log        | 3.0   | 45   | 0.4444          | 0.8596   |
+| No log        | 4.0   | 60   | 0.4205          | 0.8596   |
+| No log        | 5.0   | 75   | 0.4017          | 0.8596   |
+| No log        | 6.0   | 90   | 0.3841          | 0.8772   |
+| No log        | 7.0   | 105  | 0.3707          | 0.8772   |
+| No log        | 8.0   | 120  | 0.3595          | 0.8947   |
+| No log        | 9.0   | 135  | 0.3489          | 0.8947   |
+| No log        | 10.0  | 150  | 0.3425          | 0.8947   |
+| No log        | 11.0  | 165  | 0.3385          | 0.8947   |
+| No log        | 12.0  | 180  | 0.3371          | 0.8947   |
+
+
+### Framework versions
+
+- Transformers 4.32.1
+- Pytorch 2.3.0+cu121
+- Datasets 2.20.0
+- Tokenizers 0.13.2

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