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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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- spearmanr |
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model-index: |
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- name: mobilebert_sa_GLUE_Experiment_logit_kd_pretrain_stsb |
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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 STSB |
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type: glue |
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config: stsb |
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split: validation |
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args: stsb |
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metrics: |
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- name: Spearmanr |
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type: spearmanr |
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value: 0.8642221596976783 |
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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_sa_GLUE_Experiment_logit_kd_pretrain_stsb |
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This model is a fine-tuned version of [gokuls/mobilebert_sa_pre-training-complete](https://huggingface.co/gokuls/mobilebert_sa_pre-training-complete) on the GLUE STSB dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2919 |
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- Pearson: 0.8665 |
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- Spearmanr: 0.8642 |
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- Combined Score: 0.8654 |
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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 | Pearson | Spearmanr | Combined Score | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:| |
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| 1.1501 | 1.0 | 45 | 0.4726 | 0.7774 | 0.7922 | 0.7848 | |
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| 0.364 | 2.0 | 90 | 0.3480 | 0.8457 | 0.8455 | 0.8456 | |
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| 0.259 | 3.0 | 135 | 0.3156 | 0.8582 | 0.8590 | 0.8586 | |
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| 0.2054 | 4.0 | 180 | 0.4231 | 0.8551 | 0.8549 | 0.8550 | |
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| 0.1629 | 5.0 | 225 | 0.3245 | 0.8668 | 0.8654 | 0.8661 | |
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| 0.1263 | 6.0 | 270 | 0.3192 | 0.8649 | 0.8625 | 0.8637 | |
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| 0.1021 | 7.0 | 315 | 0.3337 | 0.8655 | 0.8629 | 0.8642 | |
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| 0.0841 | 8.0 | 360 | 0.3061 | 0.8601 | 0.8577 | 0.8589 | |
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| 0.0713 | 9.0 | 405 | 0.3600 | 0.8576 | 0.8555 | 0.8566 | |
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| 0.0587 | 10.0 | 450 | 0.3135 | 0.8620 | 0.8600 | 0.8610 | |
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| 0.0488 | 11.0 | 495 | 0.3006 | 0.8641 | 0.8620 | 0.8631 | |
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| 0.0441 | 12.0 | 540 | 0.3308 | 0.8645 | 0.8621 | 0.8633 | |
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| 0.0385 | 13.0 | 585 | 0.3468 | 0.8620 | 0.8601 | 0.8610 | |
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| 0.0346 | 14.0 | 630 | 0.3175 | 0.8658 | 0.8634 | 0.8646 | |
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| 0.0298 | 15.0 | 675 | 0.2919 | 0.8665 | 0.8642 | 0.8654 | |
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| 0.0299 | 16.0 | 720 | 0.3103 | 0.8649 | 0.8628 | 0.8639 | |
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| 0.0263 | 17.0 | 765 | 0.3325 | 0.8620 | 0.8599 | 0.8609 | |
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| 0.0237 | 18.0 | 810 | 0.3092 | 0.8636 | 0.8611 | 0.8623 | |
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| 0.0213 | 19.0 | 855 | 0.3169 | 0.8653 | 0.8631 | 0.8642 | |
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| 0.0196 | 20.0 | 900 | 0.2985 | 0.8647 | 0.8624 | 0.8636 | |
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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 2.9.0 |
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- Tokenizers 0.13.2 |
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