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--- |
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license: mit |
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tags: |
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- text-classification |
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- generated_from_trainer |
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datasets: |
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- xnli |
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metrics: |
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- accuracy |
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model-index: |
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- name: xnli_xlm_r_only_vi |
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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: xnli |
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type: xnli |
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config: vi |
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split: train |
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args: vi |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.7562248995983936 |
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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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# xnli_xlm_r_only_vi |
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the xnli dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8671 |
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- Accuracy: 0.7562 |
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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: 128 |
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- eval_batch_size: 128 |
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- seed: 42 |
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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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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 10 |
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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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| 0.6983 | 1.0 | 3068 | 0.6356 | 0.7486 | |
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| 0.5646 | 2.0 | 6136 | 0.5699 | 0.7731 | |
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| 0.5002 | 3.0 | 9204 | 0.5918 | 0.7622 | |
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| 0.4456 | 4.0 | 12272 | 0.6191 | 0.7711 | |
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| 0.3958 | 5.0 | 15340 | 0.6321 | 0.7755 | |
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| 0.3519 | 6.0 | 18408 | 0.7137 | 0.7586 | |
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| 0.3127 | 7.0 | 21476 | 0.7399 | 0.7614 | |
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| 0.2817 | 8.0 | 24544 | 0.7822 | 0.7622 | |
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| 0.256 | 9.0 | 27612 | 0.8316 | 0.7590 | |
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| 0.2362 | 10.0 | 30680 | 0.8671 | 0.7562 | |
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### Framework versions |
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- Transformers 4.24.0 |
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- Pytorch 1.13.0 |
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- Datasets 2.6.1 |
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- Tokenizers 0.13.1 |
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