---
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: add_BERT_no_pretrain_sst2
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: glue
      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
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# add_BERT_no_pretrain_sst2

This model is a fine-tuned version of [](https://huggingface.co/) on the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7002
- 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6983        | 1.0   | 527  | 0.6936          | 0.5092   |
| 0.6895        | 2.0   | 1054 | 0.7089          | 0.5092   |
| 0.6881        | 3.0   | 1581 | 0.6993          | 0.5092   |
| 0.6875        | 4.0   | 2108 | 0.6994          | 0.5092   |
| 0.6874        | 5.0   | 2635 | 0.6941          | 0.5092   |
| 0.687         | 6.0   | 3162 | 0.7002          | 0.5092   |


### Framework versions

- Transformers 4.30.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3