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--- |
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language: |
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- en |
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license: mit |
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base_model: xlm-roberta-large |
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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: xlm-roberta-large-qnli-100 |
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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/QNLI |
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type: tmnam20/VieGLUE |
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config: qnli |
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split: validation |
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args: qnli |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.4946000366099213 |
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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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# xlm-roberta-large-qnli-100 |
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This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on the tmnam20/VieGLUE/QNLI dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6932 |
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- Accuracy: 0.4946 |
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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: 100 |
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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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| 0.6979 | 1.53 | 5000 | 0.6933 | 0.4946 | |
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### Framework versions |
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- Transformers 4.36.0 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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