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--- |
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language: |
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- en |
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- ar |
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- bg |
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- de |
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- el |
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- fr |
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- hi |
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- ru |
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- es |
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- sw |
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- th |
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- tr |
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- ur |
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- vi |
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- zh |
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tags: |
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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: pixel-base-finetuned-xnli-translate-train-all |
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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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args: xnli |
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metrics: |
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- name: Joint validation accuracy |
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type: accuracy |
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value: 0.6254886211512718 |
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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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# pixel-base-finetuned-xnli-translate-train-all |
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This model is a fine-tuned version of [Team-PIXEL/pixel-base](https://huggingface.co/Team-PIXEL/pixel-base) on the XNLI dataset. |
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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: 256 |
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- eval_batch_size: 8 |
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- seed: 555 |
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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: 1000 |
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- training_steps: 50000 |
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- mixed_precision_training: Apex, opt level O1 |
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### Framework versions |
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- Transformers 4.17.0 |
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- Pytorch 1.11.0 |
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- Datasets 2.0.0 |
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- Tokenizers 0.12.1 |
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