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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_new_no_pretrain_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: 0.20926356415783265 |
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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_new_no_pretrain_stsb |
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This model is a fine-tuned version of [](https://huggingface.co/) on the GLUE STSB dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.2174 |
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- Pearson: 0.1946 |
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- Spearmanr: 0.2093 |
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- Combined Score: 0.2019 |
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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: 4e-05 |
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- train_batch_size: 128 |
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- eval_batch_size: 128 |
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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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Pearson | Spearmanr | Combined Score | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:| |
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| 2.3893 | 1.0 | 45 | 2.3698 | 0.1204 | 0.1138 | 0.1171 | |
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| 1.9589 | 2.0 | 90 | 2.2174 | 0.1946 | 0.2093 | 0.2019 | |
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| 1.6743 | 3.0 | 135 | 2.3481 | 0.2144 | 0.2207 | 0.2175 | |
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| 1.4068 | 4.0 | 180 | 2.5921 | 0.2472 | 0.2519 | 0.2496 | |
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| 1.2205 | 5.0 | 225 | 2.6279 | 0.2718 | 0.2701 | 0.2709 | |
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| 0.9353 | 6.0 | 270 | 2.5440 | 0.3117 | 0.3213 | 0.3165 | |
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| 0.7662 | 7.0 | 315 | 2.3053 | 0.3501 | 0.3519 | 0.3510 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- Pytorch 1.14.0a0+410ce96 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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