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---
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: hBERTv2_data_aug_qqp
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# hBERTv2_data_aug_qqp
This model is a fine-tuned version of [gokuls/bert_12_layer_model_v2](https://huggingface.co/gokuls/bert_12_layer_model_v2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: nan
- Accuracy: 0.6318
- F1: 0.0
- Combined Score: 0.3159
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 256
- eval_batch_size: 256
- seed: 10
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Combined Score |
|:-------------:|:-----:|:------:|:---------------:|:--------:|:---:|:--------------:|
| 0.6528 | 1.0 | 29671 | 0.6782 | 0.6318 | 0.0 | 0.3159 |
| 0.6407 | 2.0 | 59342 | nan | 0.6318 | 0.0 | 0.3159 |
| 0.0 | 3.0 | 89013 | nan | 0.6318 | 0.0 | 0.3159 |
| 0.0 | 4.0 | 118684 | nan | 0.6318 | 0.0 | 0.3159 |
| 0.0 | 5.0 | 148355 | nan | 0.6318 | 0.0 | 0.3159 |
| 0.0 | 6.0 | 178026 | nan | 0.6318 | 0.0 | 0.3159 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.14.0a0+410ce96
- Datasets 2.10.1
- Tokenizers 0.13.2
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