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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: 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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It achieves the following results on the evaluation set: |
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- Loss: 0.8312 |
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- Accuracy: 0.6255 |
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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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
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| 1.0422 | 0.04 | 1000 | 1.0647 | 0.4250 | |
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| 0.9622 | 0.09 | 2000 | 1.0015 | 0.5051 | |
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| 0.93 | 0.13 | 3000 | 0.9750 | 0.5285 | |
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| 0.9126 | 0.17 | 4000 | 0.9396 | 0.5488 | |
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| 0.9033 | 0.22 | 5000 | 0.9353 | 0.5603 | |
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| 0.8861 | 0.26 | 6000 | 0.9369 | 0.5606 | |
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| 0.8799 | 0.3 | 7000 | 0.9407 | 0.5575 | |
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| 0.8627 | 0.35 | 8000 | 0.9079 | 0.5774 | |
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| 0.8658 | 0.39 | 9000 | 0.9110 | 0.5711 | |
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| 0.8521 | 0.43 | 10000 | 0.8945 | 0.5837 | |
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| 0.8562 | 0.48 | 11000 | 0.8818 | 0.5871 | |
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| 0.8479 | 0.52 | 12000 | 0.8771 | 0.5938 | |
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| 0.8451 | 0.56 | 13000 | 0.8965 | 0.5844 | |
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| 0.8433 | 0.61 | 14000 | 0.8814 | 0.5937 | |
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| 0.8331 | 0.65 | 15000 | 0.8721 | 0.5983 | |
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| 0.8267 | 0.7 | 16000 | 0.8691 | 0.5978 | |
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| 0.8254 | 0.74 | 17000 | 0.8646 | 0.5999 | |
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| 0.8214 | 0.78 | 18000 | 0.8700 | 0.6004 | |
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| 0.815 | 0.83 | 19000 | 0.8621 | 0.6016 | |
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| 0.8145 | 0.87 | 20000 | 0.8482 | 0.6119 | |
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| 0.8067 | 0.91 | 21000 | 0.8601 | 0.6053 | |
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| 0.8063 | 0.96 | 22000 | 0.8535 | 0.6093 | |
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| 0.8008 | 1.0 | 23000 | 0.8455 | 0.6123 | |
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| 0.7863 | 1.04 | 24000 | 0.8524 | 0.6107 | |
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| 0.7918 | 1.09 | 25000 | 0.8450 | 0.6142 | |
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| 0.7746 | 1.13 | 26000 | 0.8531 | 0.6095 | |
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| 0.7855 | 1.17 | 27000 | 0.8442 | 0.6150 | |
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| 0.7903 | 1.22 | 28000 | 0.8386 | 0.6162 | |
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| 0.7808 | 1.26 | 29000 | 0.8403 | 0.6178 | |
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| 0.7847 | 1.3 | 30000 | 0.8421 | 0.6145 | |
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| 0.7822 | 1.35 | 31000 | 0.8427 | 0.6157 | |
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| 0.769 | 1.39 | 32000 | 0.8397 | 0.6187 | |
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| 0.7822 | 1.43 | 33000 | 0.8315 | 0.6213 | |
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| 0.771 | 1.48 | 34000 | 0.8505 | 0.6141 | |
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| 0.7713 | 1.52 | 35000 | 0.8482 | 0.6142 | |
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| 0.7663 | 1.56 | 36000 | 0.8490 | 0.6169 | |
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| 0.7653 | 1.61 | 37000 | 0.8295 | 0.6229 | |
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| 0.7669 | 1.65 | 38000 | 0.8313 | 0.6217 | |
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| 0.77 | 1.69 | 39000 | 0.8309 | 0.6234 | |
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| 0.763 | 1.74 | 40000 | 0.8310 | 0.6256 | |
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| 0.7609 | 1.78 | 41000 | 0.8302 | 0.6228 | |
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| 0.7627 | 1.83 | 42000 | 0.8242 | 0.6269 | |
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| 0.7617 | 1.87 | 43000 | 0.8232 | 0.6264 | |
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| 0.7636 | 1.91 | 44000 | 0.8265 | 0.6261 | |
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| 0.7585 | 1.96 | 45000 | 0.8258 | 0.6268 | |
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| 0.7572 | 2.0 | 46000 | 0.8223 | 0.6278 | |
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| 0.7396 | 2.04 | 47000 | 0.8348 | 0.6242 | |
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| 0.7344 | 2.09 | 48000 | 0.8299 | 0.6270 | |
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| 0.7385 | 2.13 | 49000 | 0.8314 | 0.6240 | |
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| 0.7275 | 2.17 | 50000 | 0.8312 | 0.6255 | |
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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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