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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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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_data_aug_stsb_128
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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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# mobilebert_sa_GLUE_Experiment_logit_kd_data_aug_stsb_128
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This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.6544
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- Pearson: 0.1506
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- Spearmanr: 0.1478
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- Combined Score: 0.1492
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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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| 0.5444 | 1.0 | 2518 | 1.4965 | 0.1589 | 0.1763 | 0.1676 |
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| 0.3254 | 2.0 | 5036 | 1.5276 | 0.1502 | 0.1674 | 0.1588 |
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| 0.2847 | 3.0 | 7554 | 1.5430 | 0.1587 | 0.1680 | 0.1634 |
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| 0.2376 | 4.0 | 10072 | 1.6906 | 0.1669 | 0.1786 | 0.1728 |
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| 0.1741 | 5.0 | 12590 | 1.4788 | 0.1662 | 0.1725 | 0.1694 |
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| 0.1315 | 6.0 | 15108 | 1.5662 | 0.1640 | 0.1700 | 0.1670 |
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| 0.1055 | 7.0 | 17626 | 1.5100 | 0.1663 | 0.1698 | 0.1680 |
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| 0.0879 | 8.0 | 20144 | 1.4602 | 0.1596 | 0.1582 | 0.1589 |
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| 0.0739 | 9.0 | 22662 | 1.6612 | 0.1584 | 0.1621 | 0.1603 |
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| 0.0632 | 10.0 | 25180 | 1.5825 | 0.1489 | 0.1547 | 0.1518 |
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| 0.0548 | 11.0 | 27698 | 1.5946 | 0.1421 | 0.1461 | 0.1441 |
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| 0.0473 | 12.0 | 30216 | 1.6515 | 0.1526 | 0.1548 | 0.1537 |
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| 0.0415 | 13.0 | 32734 | 1.6544 | 0.1506 | 0.1478 | 0.1492 |
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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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