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--- |
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language: |
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- en |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- glue |
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metrics: |
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- accuracy |
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- f1 |
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model-index: |
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- name: qqp |
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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: GLUE QQP |
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type: glue |
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args: qqp |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8988869651249073 |
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- name: F1 |
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type: f1 |
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value: 0.8670050100852366 |
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- task: |
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type: natural-language-inference |
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name: Natural Language Inference |
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dataset: |
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name: glue |
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type: glue |
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config: qqp |
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split: validation |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8989859015582489 |
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verified: true |
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- name: Precision |
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type: precision |
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value: 0.8407470502870844 |
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verified: true |
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- name: Recall |
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type: recall |
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value: 0.8951965065502183 |
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verified: true |
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- name: AUC |
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type: auc |
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value: 0.9590670523994457 |
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verified: true |
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- name: F1 |
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type: f1 |
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value: 0.8671178499381792 |
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verified: true |
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- name: loss |
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type: loss |
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value: 0.2457672506570816 |
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verified: true |
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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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# qqp |
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This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on the GLUE QQP dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2458 |
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- Accuracy: 0.8989 |
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- F1: 0.8670 |
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- Combined Score: 0.8829 |
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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: 5e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 8 |
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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: 2.5 |
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### Training results |
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### Framework versions |
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- Transformers 4.20.0.dev0 |
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- Pytorch 1.11.0 |
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- Datasets 2.2.2 |
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- Tokenizers 0.12.1 |
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