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README.md
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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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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_add_GLUE_Experiment_logit_kd_stsb_128
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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
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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: 0.07003830521003132
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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_logit_kd_stsb_128
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This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on the glue dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.2214
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- Pearson: 0.0666
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- Spearmanr: 0.0700
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- Combined Score: 0.0683
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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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| 2.524 | 1.0 | 45 | 1.3607 | -0.0066 | -0.0281 | -0.0174 |
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| 1.0877 | 2.0 | 90 | 1.1729 | 0.0446 | 0.0497 | 0.0472 |
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| 1.0648 | 3.0 | 135 | 1.1505 | 0.0470 | 0.0414 | 0.0442 |
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| 1.0737 | 4.0 | 180 | 1.1564 | 0.0472 | 0.0464 | 0.0468 |
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| 1.0445 | 5.0 | 225 | 1.1971 | 0.0529 | 0.0575 | 0.0552 |
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| 1.0296 | 6.0 | 270 | 1.1723 | 0.0578 | 0.0727 | 0.0652 |
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| 1.026 | 7.0 | 315 | 1.2735 | 0.0621 | 0.0606 | 0.0614 |
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| 1.0216 | 8.0 | 360 | 1.2214 | 0.0666 | 0.0700 | 0.0683 |
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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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