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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_mrpc
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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: mrpc
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split: validation
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args: mrpc
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.6029411764705882
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- name: F1
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type: f1
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value: 0.6908396946564885
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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_mrpc
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This model is a fine-tuned version of [gokuls/bert_12_layer_model_v2_complete_training_new_48](https://huggingface.co/gokuls/bert_12_layer_model_v2_complete_training_new_48) on the glue dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.2389
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- Accuracy: 0.6029
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- F1: 0.6908
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- Combined Score: 0.6469
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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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| 0.6634 | 1.0 | 29 | 0.6017 | 0.6863 | 0.7881 | 0.7372 |
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| 0.6054 | 2.0 | 58 | 0.6601 | 0.6691 | 0.7316 | 0.7004 |
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| 0.5623 | 3.0 | 87 | 0.5996 | 0.6936 | 0.8092 | 0.7514 |
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| 0.4773 | 4.0 | 116 | 0.6380 | 0.7010 | 0.8057 | 0.7534 |
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| 0.3781 | 5.0 | 145 | 0.8476 | 0.6471 | 0.7391 | 0.6931 |
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| 0.258 | 6.0 | 174 | 0.8257 | 0.6642 | 0.7514 | 0.7078 |
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| 0.2236 | 7.0 | 203 | 1.1873 | 0.6495 | 0.7451 | 0.6973 |
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| 0.1818 | 8.0 | 232 | 1.2389 | 0.6029 | 0.6908 | 0.6469 |
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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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