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update model card README.md
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README.md
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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: bert-base-cased-finetuned-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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args: stsb
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metrics:
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- name: Spearmanr
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type: spearmanr
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value: 0.8897907271421561
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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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# bert-base-cased-finetuned-stsb
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This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the GLUE STSB dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4861
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- Pearson: 0.8926
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- Spearmanr: 0.8898
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- Combined Score: 0.8912
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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: 2e-05
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- train_batch_size: 16
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- eval_batch_size: 8
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- seed: 42
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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: 3.0
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### Training results
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| Training Loss | Epoch | Step | Combined Score | Validation Loss | Pearson | Spearmanr |
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|:-------------:|:-----:|:----:|:--------------:|:---------------:|:-------:|:---------:|
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| 1.1174 | 1.0 | 360 | 0.8816 | 0.5000 | 0.8832 | 0.8800 |
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| 0.3835 | 2.0 | 720 | 0.8901 | 0.4672 | 0.8915 | 0.8888 |
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| 0.2388 | 3.0 | 1080 | 0.8912 | 0.4861 | 0.8926 | 0.8898 |
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### Framework versions
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- Transformers 4.11.0.dev0
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- Pytorch 1.9.0
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- Datasets 1.12.1
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- Tokenizers 0.10.3
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