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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-sst2-1
+  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-sst2-1
+
+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: 0.4333
+- 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: 1
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.3821        | 0.24  | 500  | 0.3799          | 0.8314   |
+| 0.3198        | 0.48  | 1000 | 0.4079          | 0.8417   |
+| 0.272         | 0.71  | 1500 | 0.3721          | 0.8670   |
+| 0.2847        | 0.95  | 2000 | 0.3885          | 0.8567   |
+| 0.1893        | 1.19  | 2500 | 0.4329          | 0.8589   |
+| 0.2124        | 1.43  | 3000 | 0.4133          | 0.8532   |
+| 0.2208        | 1.66  | 3500 | 0.3665          | 0.8773   |
+| 0.2219        | 1.9   | 4000 | 0.4164          | 0.8601   |
+| 0.1562        | 2.14  | 4500 | 0.4350          | 0.8635   |
+| 0.1399        | 2.38  | 5000 | 0.4571          | 0.8761   |
+| 0.1399        | 2.61  | 5500 | 0.4346          | 0.8796   |
+| 0.1403        | 2.85  | 6000 | 0.4325          | 0.8819   |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.2.0.dev20231203+cu121
+- Datasets 2.15.0
+- Tokenizers 0.15.0