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--- |
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language: |
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- en |
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license: apache-2.0 |
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base_model: bert-base-multilingual-cased |
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tags: |
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- generated_from_trainer |
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datasets: |
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- tmnam20/VieGLUE |
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metrics: |
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- accuracy |
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model-index: |
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- name: bert-base-multilingual-cased-sst2-1 |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: tmnam20/VieGLUE/SST2 |
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type: tmnam20/VieGLUE |
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config: sst2 |
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split: validation |
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args: sst2 |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8841743119266054 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# bert-base-multilingual-cased-sst2-1 |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4333 |
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- Accuracy: 0.8842 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 16 |
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- seed: 1 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 3.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 0.3821 | 0.24 | 500 | 0.3799 | 0.8314 | |
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| 0.3198 | 0.48 | 1000 | 0.4079 | 0.8417 | |
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| 0.272 | 0.71 | 1500 | 0.3721 | 0.8670 | |
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| 0.2847 | 0.95 | 2000 | 0.3885 | 0.8567 | |
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| 0.1893 | 1.19 | 2500 | 0.4329 | 0.8589 | |
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| 0.2124 | 1.43 | 3000 | 0.4133 | 0.8532 | |
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| 0.2208 | 1.66 | 3500 | 0.3665 | 0.8773 | |
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| 0.2219 | 1.9 | 4000 | 0.4164 | 0.8601 | |
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| 0.1562 | 2.14 | 4500 | 0.4350 | 0.8635 | |
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| 0.1399 | 2.38 | 5000 | 0.4571 | 0.8761 | |
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| 0.1399 | 2.61 | 5500 | 0.4346 | 0.8796 | |
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| 0.1403 | 2.85 | 6000 | 0.4325 | 0.8819 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.2.0.dev20231203+cu121 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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