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--- |
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language: |
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- en |
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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: add_BERT_no_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: 0.017883010860882925 |
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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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# add_BERT_no_pretrain_stsb |
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This model is a fine-tuned version of [](https://huggingface.co/) on the GLUE STSB dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.2521 |
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- Pearson: 0.0142 |
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- Spearmanr: 0.0179 |
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- Combined Score: 0.0161 |
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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: 0.0005 |
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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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- mixed_precision_training: Native AMP |
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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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| 6.3185 | 1.0 | 45 | 2.7648 | 0.0033 | -0.0054 | -0.0010 | |
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| 2.2915 | 2.0 | 90 | 2.2692 | 0.0207 | 0.0100 | 0.0154 | |
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| 2.2747 | 3.0 | 135 | 2.3623 | 0.0167 | 0.0040 | 0.0103 | |
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| 2.2372 | 4.0 | 180 | 2.8836 | 0.0090 | 0.0044 | 0.0067 | |
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| 2.2573 | 5.0 | 225 | 2.2528 | 0.0337 | 0.0365 | 0.0351 | |
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| 2.1979 | 6.0 | 270 | 2.2521 | 0.0142 | 0.0179 | 0.0161 | |
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| 2.2244 | 7.0 | 315 | 2.3162 | 0.0157 | 0.0189 | 0.0173 | |
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| 2.1832 | 8.0 | 360 | 2.3739 | 0.0006 | 0.0039 | 0.0023 | |
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| 2.3249 | 9.0 | 405 | 2.3829 | nan | nan | nan | |
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| 2.1956 | 10.0 | 450 | 2.3083 | nan | nan | nan | |
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| 2.2148 | 11.0 | 495 | 2.2706 | -0.0283 | -0.0268 | -0.0276 | |
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### Framework versions |
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- Transformers 4.29.2 |
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- Pytorch 1.14.0a0+410ce96 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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