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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_48_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: 0.750517182024731
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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_48_stsb
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This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48) on the glue dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.0470
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- Pearson: 0.7517
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- Spearmanr: 0.7505
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- Combined Score: 0.7511
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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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| 2.5456 | 1.0 | 45 | 2.2706 | 0.1246 | 0.1141 | 0.1194 |
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| 2.0514 | 2.0 | 90 | 2.0613 | 0.5266 | 0.5198 | 0.5232 |
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| 1.3837 | 3.0 | 135 | 1.1984 | 0.6853 | 0.6942 | 0.6897 |
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| 1.0297 | 4.0 | 180 | 1.6176 | 0.6869 | 0.6961 | 0.6915 |
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| 0.8064 | 5.0 | 225 | 1.1444 | 0.7476 | 0.7445 | 0.7460 |
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| 0.604 | 6.0 | 270 | 1.2754 | 0.7422 | 0.7450 | 0.7436 |
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| 0.4818 | 7.0 | 315 | 1.1407 | 0.7687 | 0.7673 | 0.7680 |
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| 0.3905 | 8.0 | 360 | 1.1860 | 0.7560 | 0.7604 | 0.7582 |
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| 0.3476 | 9.0 | 405 | 0.9800 | 0.7515 | 0.7472 | 0.7493 |
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| 0.2819 | 10.0 | 450 | 1.0156 | 0.7521 | 0.7507 | 0.7514 |
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| 0.2418 | 11.0 | 495 | 1.0174 | 0.7516 | 0.7480 | 0.7498 |
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| 0.2068 | 12.0 | 540 | 1.2367 | 0.7530 | 0.7523 | 0.7527 |
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| 0.1863 | 13.0 | 585 | 1.0073 | 0.7491 | 0.7468 | 0.7480 |
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| 0.1929 | 14.0 | 630 | 1.0470 | 0.7517 | 0.7505 | 0.7511 |
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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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