transformers pytorch tensorboard deberta-v2 text-classification generated_from_trainer dataset:super_glue license:mit model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- super_glue
license: mit
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: finetune_deberta_small_model
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: super_glue
      type: super_glue
      config: boolq
      split: train
      args: boolq
    metrics:
    - type: accuracy
      value: 0.8021406727828746
      name: Accuracy
---

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# finetune_deberta_small_model

This model is a fine-tuned version of [nc33/finetune_deberta_small_model](https://huggingface.co/nc33/finetune_deberta_small_model) on the super_glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6788
- Accuracy: 0.8021

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3666        | 1.0   | 590  | 0.5625          | 0.8003   |
| 0.2501        | 2.0   | 1180 | 0.6762          | 0.7976   |
| 0.2343        | 3.0   | 1770 | 0.6788          | 0.8021   |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2
