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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_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 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: 0.041438738522880283 |
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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 STSB dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1505 |
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- Pearson: 0.0470 |
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- Spearmanr: 0.0414 |
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- Combined Score: 0.0442 |
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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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