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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: mobilebert_add_GLUE_Experiment_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: 0.7599802127133317 |
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- name: F1 |
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type: f1 |
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value: 0.6401928068223952 |
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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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# mobilebert_add_GLUE_Experiment_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: 0.5008 |
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- Accuracy: 0.7600 |
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- F1: 0.6402 |
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- Combined Score: 0.7001 |
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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: 128 |
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- eval_batch_size: 128 |
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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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| 0.6505 | 1.0 | 2843 | 0.6498 | 0.6321 | 0.0012 | 0.3166 | |
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| 0.6474 | 2.0 | 5686 | 0.6484 | 0.6321 | 0.0012 | 0.3166 | |
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| 0.646 | 3.0 | 8529 | 0.6479 | 0.6322 | 0.0024 | 0.3173 | |
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| 0.5481 | 4.0 | 11372 | 0.5140 | 0.7486 | 0.6247 | 0.6867 | |
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| 0.4934 | 5.0 | 14215 | 0.5086 | 0.7529 | 0.6548 | 0.7039 | |
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| 0.4794 | 6.0 | 17058 | 0.5044 | 0.7575 | 0.6527 | 0.7051 | |
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| 0.4708 | 7.0 | 19901 | 0.5008 | 0.7600 | 0.6402 | 0.7001 | |
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| 0.4652 | 8.0 | 22744 | 0.5010 | 0.7619 | 0.6384 | 0.7001 | |
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| 0.4604 | 9.0 | 25587 | 0.5014 | 0.7614 | 0.6489 | 0.7052 | |
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| 0.4562 | 10.0 | 28430 | 0.5057 | 0.7600 | 0.6617 | 0.7108 | |
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| 0.452 | 11.0 | 31273 | 0.5102 | 0.7620 | 0.6364 | 0.6992 | |
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| 0.4476 | 12.0 | 34116 | 0.5302 | 0.7622 | 0.6619 | 0.7121 | |
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### Framework versions |
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- Transformers 4.26.0 |
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- Pytorch 1.14.0a0+410ce96 |
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- Datasets 2.8.0 |
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- Tokenizers 0.13.2 |
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