transformers pytorch tensorboard hybridbert text-classification generated_from_trainer en dataset:glue model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- glue
language:
- en
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: hBERTv2_sst2
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE SST2
      type: glue
      config: sst2
      split: validation
      args: sst2
    metrics:
    - type: accuracy
      value: 0.5091743119266054
      name: Accuracy
---

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# 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
