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--- |
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language: |
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- en |
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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: hBERTv1_no_pretrain_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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config: qqp |
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split: validation |
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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: 0.7953747217412812 |
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- name: F1 |
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type: f1 |
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value: 0.7269366603954186 |
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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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# hBERTv1_no_pretrain_qqp |
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This model is a fine-tuned version of [](https://huggingface.co/) on the GLUE QQP dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4402 |
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- Accuracy: 0.7954 |
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- F1: 0.7269 |
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- Combined Score: 0.7612 |
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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: 4e-05 |
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- train_batch_size: 96 |
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- eval_batch_size: 96 |
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- seed: 10 |
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- distributed_type: multi-GPU |
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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: 50 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Combined Score | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:| |
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| 0.5334 | 1.0 | 3791 | 0.4826 | 0.7676 | 0.6650 | 0.7163 | |
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| 0.4491 | 2.0 | 7582 | 0.4493 | 0.7909 | 0.6926 | 0.7417 | |
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| 0.3866 | 3.0 | 11373 | 0.4402 | 0.7954 | 0.7269 | 0.7612 | |
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| 0.3657 | 4.0 | 15164 | 0.4990 | 0.7775 | 0.7211 | 0.7493 | |
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| 0.3708 | 5.0 | 18955 | 0.4744 | 0.8077 | 0.7273 | 0.7675 | |
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| 0.2948 | 6.0 | 22746 | 0.4693 | 0.8143 | 0.7379 | 0.7761 | |
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| 0.2546 | 7.0 | 26537 | 0.4507 | 0.8120 | 0.7578 | 0.7849 | |
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| 0.2225 | 8.0 | 30328 | 0.5245 | 0.8193 | 0.7511 | 0.7852 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- Pytorch 1.14.0a0+410ce96 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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