---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- sst2
metrics:
- accuracy
model-index:
- name: bert-base-uncased-sst2
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: sst2
      type: sst2
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.876
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert-base-uncased-sst2

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the sst2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9312
- Accuracy: 0.876

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 125  | 1.0209          | 0.836    |
| No log        | 2.0   | 250  | 1.0430          | 0.85     |
| No log        | 3.0   | 375  | 0.9312          | 0.876    |


### Framework versions

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