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--- |
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tags: |
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- generated_from_trainer |
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datasets: |
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- subjqa |
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model-index: |
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- name: qa_bert-base-multilingual-cased-finetuned-squad |
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results: [] |
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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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# qa_bert-base-multilingual-cased-finetuned-squad |
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This model is a fine-tuned version of [salti/bert-base-multilingual-cased-finetuned-squad](https://huggingface.co/salti/bert-base-multilingual-cased-finetuned-squad) on the subjqa dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.8327 |
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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: 1e-06 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 2.6495 | 1.0 | 81 | 2.3399 | |
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| 1.8855 | 2.0 | 162 | 2.0887 | |
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| 1.7301 | 3.0 | 243 | 1.9716 | |
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| 1.668 | 4.0 | 324 | 1.9215 | |
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| 1.6121 | 5.0 | 405 | 1.8922 | |
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| 1.5587 | 6.0 | 486 | 1.8767 | |
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| 1.5236 | 7.0 | 567 | 1.8614 | |
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| 1.4978 | 8.0 | 648 | 1.8464 | |
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| 1.4769 | 9.0 | 729 | 1.8434 | |
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| 1.4612 | 10.0 | 810 | 1.8364 | |
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| 1.4215 | 11.0 | 891 | 1.8357 | |
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| 1.4132 | 12.0 | 972 | 1.8330 | |
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| 1.394 | 13.0 | 1053 | 1.8325 | |
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| 1.3798 | 14.0 | 1134 | 1.8348 | |
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| 1.3786 | 15.0 | 1215 | 1.8326 | |
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| 1.3668 | 16.0 | 1296 | 1.8339 | |
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| 1.3545 | 17.0 | 1377 | 1.8338 | |
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| 1.3581 | 18.0 | 1458 | 1.8323 | |
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| 1.3449 | 19.0 | 1539 | 1.8324 | |
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| 1.3443 | 20.0 | 1620 | 1.8327 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.10.1 |
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- Tokenizers 0.13.2 |
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