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---
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: hBERTv2_new_no_pretrain_qnli
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE QNLI
type: glue
config: qnli
split: validation
args: qnli
metrics:
- name: Accuracy
type: accuracy
value: 0.6351821343584111
---
<!-- 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_new_no_pretrain_qnli
This model is a fine-tuned version of [](https://huggingface.co/) on the GLUE QNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6386
- Accuracy: 0.6352
## 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: 4e-05
- train_batch_size: 128
- eval_batch_size: 128
- 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
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6866 | 1.0 | 819 | 0.6770 | 0.5570 |
| 0.652 | 2.0 | 1638 | 0.6468 | 0.6264 |
| 0.5986 | 3.0 | 2457 | 0.6386 | 0.6352 |
| 0.5144 | 4.0 | 3276 | 0.6930 | 0.6590 |
| 0.4272 | 5.0 | 4095 | 0.7034 | 0.6548 |
| 0.3558 | 6.0 | 4914 | 0.8171 | 0.6637 |
| 0.2874 | 7.0 | 5733 | 0.9057 | 0.6601 |
| 0.2391 | 8.0 | 6552 | 1.0090 | 0.6445 |
### Framework versions
- Transformers 4.30.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3
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