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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_no_pretrain_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: 0.6318327974276527
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- name: F1
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type: f1
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value: 0.0
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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_no_pretrain_qqp
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This model is a fine-tuned version of [](https://huggingface.co/) on the glue dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6580
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- Accuracy: 0.6318
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- F1: 0.0
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- Combined Score: 0.3159
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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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- mixed_precision_training: Native AMP
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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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| 0.6669 | 1.0 | 2843 | 0.6595 | 0.6318 | 0.0 | 0.3159 |
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| 0.6591 | 2.0 | 5686 | 0.6587 | 0.6318 | 0.0 | 0.3159 |
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| 0.6589 | 3.0 | 8529 | 0.6582 | 0.6318 | 0.0 | 0.3159 |
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| 0.6587 | 4.0 | 11372 | 0.6580 | 0.6318 | 0.0 | 0.3159 |
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| 0.6586 | 5.0 | 14215 | 0.6579 | 0.6318 | 0.0 | 0.3159 |
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| 0.6586 | 6.0 | 17058 | 0.6580 | 0.6318 | 0.0 | 0.3159 |
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| 0.6586 | 7.0 | 19901 | 0.6580 | 0.6318 | 0.0 | 0.3159 |
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| 0.6586 | 8.0 | 22744 | 0.6579 | 0.6318 | 0.0 | 0.3159 |
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| 0.6586 | 9.0 | 25587 | 0.6580 | 0.6318 | 0.0 | 0.3159 |
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| 0.6586 | 10.0 | 28430 | 0.6580 | 0.6318 | 0.0 | 0.3159 |
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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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