End of training

README.md

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+---
+license: apache-2.0
+base_model: google-bert/bert-base-multilingual-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: bert-base-multilingual-uncased-classification
+  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-base-multilingual-uncased-classification
+
+This model is a fine-tuned version of [google-bert/bert-base-multilingual-uncased](https://huggingface.co/google-bert/bert-base-multilingual-uncased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1524
+- Accuracy: 0.9642
+
+## 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: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 95   | 0.1662          | 0.9543   |
+| No log        | 2.0   | 190  | 0.2257          | 0.9523   |
+| No log        | 3.0   | 285  | 0.1605          | 0.9602   |
+| No log        | 4.0   | 380  | 0.1230          | 0.9622   |
+| No log        | 5.0   | 475  | 0.1428          | 0.9642   |
+| 0.1204        | 6.0   | 570  | 0.1545          | 0.9622   |
+| 0.1204        | 7.0   | 665  | 0.1606          | 0.9622   |
+| 0.1204        | 8.0   | 760  | 0.1432          | 0.9622   |
+| 0.1204        | 9.0   | 855  | 0.1512          | 0.9622   |
+| 0.1204        | 10.0  | 950  | 0.1524          | 0.9642   |
+
+
+### Framework versions
+
+- Transformers 4.37.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.17.1
+- Tokenizers 0.15.2

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