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---
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: hBERTv2_sst2
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE SST2
type: glue
config: sst2
split: validation
args: sst2
metrics:
- name: Accuracy
type: accuracy
value: 0.5091743119266054
---
<!-- 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_sst2
This model is a fine-tuned version of [gokuls/bert_12_layer_model_v2](https://huggingface.co/gokuls/bert_12_layer_model_v2) on the GLUE SST2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6964
- Accuracy: 0.5092
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6916 | 1.0 | 264 | 0.6999 | 0.5092 |
| 0.6885 | 2.0 | 528 | 0.6978 | 0.5092 |
| 0.6871 | 3.0 | 792 | 0.6984 | 0.5092 |
| 0.6869 | 4.0 | 1056 | 0.6990 | 0.5092 |
| 0.6868 | 5.0 | 1320 | 0.6974 | 0.5092 |
| 0.6869 | 6.0 | 1584 | 0.6980 | 0.5092 |
| 0.6867 | 7.0 | 1848 | 0.6984 | 0.5092 |
| 0.6868 | 8.0 | 2112 | 0.6975 | 0.5092 |
| 0.6868 | 9.0 | 2376 | 0.6964 | 0.5092 |
| 0.6865 | 10.0 | 2640 | 0.6978 | 0.5092 |
| 0.6868 | 11.0 | 2904 | 0.6980 | 0.5092 |
| 0.6865 | 12.0 | 3168 | 0.7001 | 0.5092 |
| 0.6867 | 13.0 | 3432 | 0.6966 | 0.5092 |
| 0.6867 | 14.0 | 3696 | 0.6980 | 0.5092 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.14.0a0+410ce96
- Datasets 2.10.1
- Tokenizers 0.13.2
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