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README.md
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---
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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: hBERTv2_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
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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: 0.7823687091799434
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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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# hBERTv2_stsb
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This model is a fine-tuned version of [gokuls/bert_12_layer_model_v2](https://huggingface.co/gokuls/bert_12_layer_model_v2) on the glue dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.1525
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- Pearson: 0.7836
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- Spearmanr: 0.7824
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- Combined Score: 0.7830
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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: 256
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- eval_batch_size: 256
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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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| 4.4386 | 1.0 | 23 | 2.5331 | 0.1313 | 0.1071 | 0.1192 |
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| 1.8741 | 2.0 | 46 | 2.0517 | 0.4923 | 0.4766 | 0.4844 |
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| 1.347 | 3.0 | 69 | 1.3556 | 0.6964 | 0.7079 | 0.7022 |
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| 0.8443 | 4.0 | 92 | 1.2583 | 0.7340 | 0.7367 | 0.7353 |
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| 0.5822 | 5.0 | 115 | 0.9534 | 0.7722 | 0.7707 | 0.7714 |
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| 0.4356 | 6.0 | 138 | 1.1921 | 0.7798 | 0.7771 | 0.7785 |
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| 0.3531 | 7.0 | 161 | 1.3849 | 0.7701 | 0.7700 | 0.7700 |
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| 0.2712 | 8.0 | 184 | 1.0015 | 0.7886 | 0.7870 | 0.7878 |
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| 0.259 | 9.0 | 207 | 1.0523 | 0.7898 | 0.7874 | 0.7886 |
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| 0.2003 | 10.0 | 230 | 1.1525 | 0.7836 | 0.7824 | 0.7830 |
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### Framework versions
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- Transformers 4.26.1
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- Pytorch 1.14.0a0+410ce96
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- Datasets 2.10.1
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- Tokenizers 0.13.2
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