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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: hBERTv1_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: 0.6941784502109372
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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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# hBERTv1_stsb
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This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1](https://huggingface.co/gokuls/bert_12_layer_model_v1) on the glue dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.2614
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- Pearson: 0.6982
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- Spearmanr: 0.6942
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- Combined Score: 0.6962
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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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| 4.0796 | 1.0 | 23 | 2.3017 | 0.0761 | 0.0547 | 0.0654 |
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| 2.0746 | 2.0 | 46 | 2.6181 | 0.0850 | 0.0772 | 0.0811 |
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| 1.9142 | 3.0 | 69 | 2.2963 | 0.1878 | 0.1852 | 0.1865 |
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| 1.6883 | 4.0 | 92 | 2.1866 | 0.4740 | 0.4777 | 0.4759 |
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| 1.1166 | 5.0 | 115 | 1.9367 | 0.6319 | 0.6450 | 0.6384 |
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| 0.7598 | 6.0 | 138 | 1.4188 | 0.6801 | 0.6888 | 0.6845 |
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| 0.5453 | 7.0 | 161 | 1.2720 | 0.6988 | 0.7001 | 0.6994 |
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| 0.3705 | 8.0 | 184 | 1.1154 | 0.7159 | 0.7156 | 0.7157 |
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| 0.2976 | 9.0 | 207 | 1.6889 | 0.6754 | 0.6807 | 0.6780 |
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| 0.2272 | 10.0 | 230 | 1.3627 | 0.6929 | 0.6899 | 0.6914 |
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| 0.1966 | 11.0 | 253 | 1.1278 | 0.7195 | 0.7167 | 0.7181 |
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| 0.1708 | 12.0 | 276 | 1.3476 | 0.7171 | 0.7165 | 0.7168 |
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| 0.1529 | 13.0 | 299 | 1.2614 | 0.6982 | 0.6942 | 0.6962 |
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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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