---
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
datasets:
- yelp_review_full
metrics:
- accuracy
model-index:
- name: ft_bert_base_cased
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: yelp_review_full
      type: yelp_review_full
      config: yelp_review_full
      split: test
      args: yelp_review_full
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.566
---

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

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the yelp_review_full dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0124
- Accuracy: 0.566

## 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: 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: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 63   | 1.1082          | 0.552    |
| No log        | 2.0   | 126  | 1.0124          | 0.566    |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.0.0
- Datasets 2.15.0
- Tokenizers 0.14.1