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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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- accuracy
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- f1
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model-index:
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- name: hBERTv2_new_pretrain_48_KD_w_init_qqp
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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: qqp
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split: validation
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args: qqp
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.7147909967845659
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- name: F1
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type: f1
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value: 0.5017069270990883
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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_pretrain_48_KD_w_init_qqp
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This model is a fine-tuned version of [gokuls/bert_12_layer_model_v2_complete_training_new_48_KD_wt_init](https://huggingface.co/gokuls/bert_12_layer_model_v2_complete_training_new_48_KD_wt_init) on the glue dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5929
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- Accuracy: 0.7148
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- F1: 0.5017
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- Combined Score: 0.6082
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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 | Accuracy | F1 | Combined Score |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
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| 0.5751 | 1.0 | 2843 | 0.5381 | 0.7260 | 0.6367 | 0.6813 |
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| 0.522 | 2.0 | 5686 | 0.5377 | 0.7336 | 0.6479 | 0.6907 |
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| 0.5274 | 3.0 | 8529 | 0.5656 | 0.7333 | 0.6147 | 0.6740 |
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| 0.5435 | 4.0 | 11372 | 0.5561 | 0.7424 | 0.6314 | 0.6869 |
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| 0.5405 | 5.0 | 14215 | 0.5772 | 0.7359 | 0.5543 | 0.6451 |
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| 0.5468 | 6.0 | 17058 | 0.5563 | 0.7355 | 0.5944 | 0.6649 |
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| 0.5732 | 7.0 | 19901 | 0.5929 | 0.7148 | 0.5017 | 0.6082 |
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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 2.13.0
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- Tokenizers 0.13.3
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