---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: distilbert_sa_GLUE_Experiment_data_aug_qnli_384
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE QNLI
      type: glue
      args: qnli
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.5701995240710233
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilbert_sa_GLUE_Experiment_data_aug_qnli_384

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the GLUE QNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0828
- Accuracy: 0.5702

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.4167        | 1.0   | 16604 | 1.0828          | 0.5702   |
| 0.1701        | 2.0   | 33208 | 1.3572          | 0.5731   |
| 0.0922        | 3.0   | 49812 | 1.7374          | 0.5797   |
| 0.0536        | 4.0   | 66416 | 1.6715          | 0.5817   |
| 0.0342        | 5.0   | 83020 | 1.9660          | 0.5817   |
| 0.0242        | 6.0   | 99624 | 2.1939          | 0.5821   |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.9.0
- Tokenizers 0.13.2