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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: 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 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: 0.7706783096515127 |
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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 STSB dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9534 |
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- Pearson: 0.7722 |
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- Spearmanr: 0.7707 |
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- Combined Score: 0.7714 |
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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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