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--- |
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license: apache-2.0 |
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base_model: google-bert/bert-base-cased |
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tags: |
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- question-answering |
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- nlp |
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- generated_from_trainer |
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model-index: |
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- name: bert-base-cased-qa-mash-covid |
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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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# bert-base-cased-qa-mash-covid |
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This model is a fine-tuned version of [google-bert/bert-base-cased](https://huggingface.co./google-bert/bert-base-cased) on the mashqa_covid_dataset dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5140 |
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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: 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: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 0.9322 | 1.0 | 2822 | 0.5217 | |
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| 0.7455 | 2.0 | 5644 | 0.5090 | |
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| 0.5868 | 3.0 | 8466 | 0.5140 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.1.2 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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