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README.md
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---
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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_w_init__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
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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: -0.014776116124505849
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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_w_init__stsb
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This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_wt_init](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_wt_init) on the glue dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.2834
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- Pearson: 0.0372
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- Spearmanr: -0.0148
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- Combined Score: 0.0112
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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: 0.0005
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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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| 61.8804 | 1.0 | 45 | 2.3512 | -0.0440 | 0.0212 | -0.0114 |
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| 2.6713 | 2.0 | 90 | 3.0563 | 0.0479 | 0.0125 | 0.0302 |
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| 2.3803 | 3.0 | 135 | 2.2578 | 0.0646 | 0.0638 | 0.0642 |
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| 2.2516 | 4.0 | 180 | 2.3252 | 0.0646 | 0.0638 | 0.0642 |
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| 2.243 | 5.0 | 225 | 2.2928 | 0.0646 | 0.0638 | 0.0642 |
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| 2.1764 | 6.0 | 270 | 2.2826 | 0.0632 | 0.0058 | 0.0345 |
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| 2.1933 | 7.0 | 315 | 2.3738 | 0.0495 | 0.0497 | 0.0496 |
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| 2.2067 | 8.0 | 360 | 2.2834 | 0.0372 | -0.0148 | 0.0112 |
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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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