---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model_index:
- name: bert-base-uncased-finetuned-sst2
  results:
  - dataset:
      name: glue
      type: glue
      args: sst2
    metric:
      name: Accuracy
      type: accuracy
      value: 0.930045871559633
---

<!-- 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-sst2

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4079
- Accuracy: 0.9300

## 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

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.1793        | 1.0   | 4210  | 0.3598          | 0.9094   |
| 0.1243        | 2.0   | 8420  | 0.3021          | 0.9243   |
| 0.0799        | 3.0   | 12630 | 0.3473          | 0.9220   |
| 0.0641        | 4.0   | 16840 | 0.3309          | 0.9289   |
| 0.0346        | 5.0   | 21050 | 0.4079          | 0.9300   |


### Framework versions

- Transformers 4.9.1
- Pytorch 1.9.0+cu102
- Datasets 1.11.0
- Tokenizers 0.10.3