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README.md

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+---
+language:
+- en
+license: apache-2.0
+base_model: bert-base-multilingual-cased
+tags:
+- generated_from_trainer
+datasets:
+- tmnam20/VieGLUE
+metrics:
+- accuracy
+model-index:
+- name: bert-base-multilingual-cased-sst2-10
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: tmnam20/VieGLUE/SST2
+      type: tmnam20/VieGLUE
+      config: sst2
+      split: validation
+      args: sst2
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8841743119266054
+---
+
+<!-- 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-cased-sst2-10
+
+This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the tmnam20/VieGLUE/SST2 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4234
+- Accuracy: 0.8842
+
+## 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: 32
+- eval_batch_size: 16
+- seed: 10
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3.0
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.4066        | 0.24  | 500  | 0.3869          | 0.8291   |
+| 0.3414        | 0.48  | 1000 | 0.3499          | 0.8486   |
+| 0.3133        | 0.71  | 1500 | 0.3743          | 0.8509   |
+| 0.2797        | 0.95  | 2000 | 0.4119          | 0.8475   |
+| 0.236         | 1.19  | 2500 | 0.3891          | 0.8670   |
+| 0.2202        | 1.43  | 3000 | 0.3640          | 0.8739   |
+| 0.1889        | 1.66  | 3500 | 0.3829          | 0.8681   |
+| 0.1847        | 1.9   | 4000 | 0.3687          | 0.8796   |
+| 0.1288        | 2.14  | 4500 | 0.4524          | 0.8807   |
+| 0.1478        | 2.38  | 5000 | 0.4259          | 0.875    |
+| 0.1761        | 2.61  | 5500 | 0.4060          | 0.8819   |
+| 0.1487        | 2.85  | 6000 | 0.4408          | 0.8807   |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.2.0.dev20231203+cu121
+- Datasets 2.15.0
+- Tokenizers 0.15.0