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--- |
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language: |
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- en |
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base_model: google-t5/t5-base |
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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: 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: 0.8871816808599587 |
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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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# STSB |
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This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-base) on the GLUE STSB dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5496 |
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- Pearson: 0.8882 |
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- Spearmanr: 0.8872 |
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- Combined Score: 0.8877 |
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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: 32 |
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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: 10.0 |
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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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| No log | 1.0 | 180 | 0.8180 | 1.1720 | 0.8128 | 0.8233 | |
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| No log | 2.0 | 360 | 0.8588 | 0.7424 | 0.8585 | 0.8591 | |
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| 1.0195 | 3.0 | 540 | 0.8756 | 0.6313 | 0.8756 | 0.8756 | |
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| 1.0195 | 4.0 | 720 | 0.8803 | 0.5849 | 0.8801 | 0.8806 | |
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| 1.0195 | 5.0 | 900 | 0.8833 | 0.6234 | 0.8838 | 0.8827 | |
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| 0.315 | 6.0 | 1080 | 0.8859 | 0.6469 | 0.8864 | 0.8854 | |
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| 0.315 | 7.0 | 1260 | 0.8861 | 0.5571 | 0.8866 | 0.8856 | |
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| 0.315 | 8.0 | 1440 | 0.8869 | 0.5629 | 0.8877 | 0.8862 | |
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| 0.2087 | 9.0 | 1620 | 0.8877 | 0.5569 | 0.8882 | 0.8871 | |
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| 0.2087 | 10.0 | 1800 | 0.8877 | 0.5496 | 0.8882 | 0.8872 | |
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### Framework versions |
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- Transformers 4.43.3 |
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- Pytorch 1.11.0+cu113 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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