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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: hBERTv1_new_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: 0.24765283238401 |
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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_new_pretrain_stsb |
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This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new) on the GLUE STSB dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.2275 |
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- Pearson: 0.2386 |
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- Spearmanr: 0.2477 |
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- Combined Score: 0.2431 |
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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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| 2.2918 | 1.0 | 45 | 2.6098 | 0.1233 | 0.1129 | 0.1181 | |
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| 1.9907 | 2.0 | 90 | 2.4074 | 0.2000 | 0.1874 | 0.1937 | |
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| 1.6996 | 3.0 | 135 | 2.2275 | 0.2386 | 0.2477 | 0.2431 | |
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| 1.4403 | 4.0 | 180 | 2.5775 | 0.3060 | 0.3062 | 0.3061 | |
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| 1.1707 | 5.0 | 225 | 2.3220 | 0.3500 | 0.3356 | 0.3428 | |
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| 0.8313 | 6.0 | 270 | 2.4218 | 0.3881 | 0.3929 | 0.3905 | |
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| 0.6374 | 7.0 | 315 | 2.2601 | 0.3980 | 0.3955 | 0.3967 | |
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| 0.5371 | 8.0 | 360 | 2.6668 | 0.3626 | 0.3601 | 0.3614 | |
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### Framework versions |
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- Transformers 4.29.2 |
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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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