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--- |
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license: mit |
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base_model: timpal0l/mdeberta-v3-base-squad2 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- covid_qa_deepset |
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model-index: |
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- name: bert-covidqa-5 |
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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-covidqa-5 |
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This model is a fine-tuned version of [timpal0l/mdeberta-v3-base-squad2](https://huggingface.co/timpal0l/mdeberta-v3-base-squad2) on the covid_qa_deepset dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4190 |
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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: 3e-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: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 0.5956 | 0.04 | 5 | 0.4016 | |
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| 0.3741 | 0.09 | 10 | 0.3879 | |
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| 0.3405 | 0.13 | 15 | 0.4240 | |
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| 0.4372 | 0.18 | 20 | 0.4102 | |
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| 0.2592 | 0.22 | 25 | 0.4534 | |
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| 0.3534 | 0.26 | 30 | 0.4571 | |
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| 0.4268 | 0.31 | 35 | 0.4107 | |
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| 0.2663 | 0.35 | 40 | 0.4166 | |
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| 0.143 | 0.39 | 45 | 0.4345 | |
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| 0.2494 | 0.44 | 50 | 0.5575 | |
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| 0.8953 | 0.48 | 55 | 0.6172 | |
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| 0.5504 | 0.53 | 60 | 0.4879 | |
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| 0.6411 | 0.57 | 65 | 0.3718 | |
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| 0.5454 | 0.61 | 70 | 0.3929 | |
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| 0.4441 | 0.66 | 75 | 0.3641 | |
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| 0.2922 | 0.7 | 80 | 0.3638 | |
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| 0.491 | 0.75 | 85 | 0.3785 | |
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| 0.4362 | 0.79 | 90 | 0.3938 | |
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| 0.1633 | 0.83 | 95 | 0.4162 | |
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| 0.6762 | 0.88 | 100 | 0.4321 | |
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| 0.3111 | 0.92 | 105 | 0.4241 | |
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| 0.3453 | 0.96 | 110 | 0.4190 | |
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### Framework versions |
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- Transformers 4.34.1 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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