---
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: bert-base-uncased-finetuned-mnli-512-10
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: glue
      type: glue
      args: mnli
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9355947399880454
---

<!-- 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. -->

# bert-base-uncased-finetuned-mnli-512-10

This model is a fine-tuned version of [yy642/bert-base-uncased-finetuned-mnli-512-5](https://huggingface.co/yy642/bert-base-uncased-finetuned-mnli-512-5) on the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4991
- Accuracy: 0.9356

## 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: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.0514        | 1.0   | 16363 | 0.4557          | 0.9265   |
| 0.0369        | 2.0   | 32726 | 0.4548          | 0.9323   |
| 0.0249        | 3.0   | 49089 | 0.4376          | 0.9320   |
| 0.0197        | 4.0   | 65452 | 0.4991          | 0.9356   |
| 0.0135        | 5.0   | 81815 | 0.5424          | 0.9341   |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.11.0a0+17540c5
- Datasets 2.0.0
- Tokenizers 0.11.6
