---
language:
- en
base_model: FacebookAI/roberta-large
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: QNLI
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE QNLI
      type: glue
      args: qnli
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9450851180669961
---

<!-- 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. -->

# QNLI

This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on the GLUE QNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2250
- Accuracy: 0.9451

## 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: 64
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2269        | 1.0   | 1637 | 0.1639          | 0.9363   |
| 0.1637        | 2.0   | 3274 | 0.1718          | 0.9372   |
| 0.0977        | 3.0   | 4911 | 0.1788          | 0.9425   |
| 0.0672        | 4.0   | 6548 | 0.2250          | 0.9451   |
| 0.0437        | 5.0   | 8185 | 0.2863          | 0.9431   |
| 0.0289        | 6.0   | 9822 | 0.3216          | 0.9438   |


### Framework versions

- Transformers 4.43.3
- Pytorch 1.11.0+cu113
- Datasets 2.20.0
- Tokenizers 0.19.1