transformers pytorch bert text-classification generated_from_trainer dataset:yelp_review_full base_model:google-bert/bert-base-cased base_model:finetune:google-bert/bert-base-cased license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: bert-base-cased
datasets:
- yelp_review_full
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: test_trainer
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: yelp_review_full
      type: yelp_review_full
      config: yelp_review_full
      split: test
      args: yelp_review_full
    metrics:
    - type: accuracy
      value: 0.587
      name: Accuracy
---

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# test_trainer

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: 1.0743
- Accuracy: 0.587

## 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  | 1.1536          | 0.525    |
| No log        | 2.0   | 250  | 1.0075          | 0.565    |
| No log        | 3.0   | 375  | 1.0743          | 0.587    |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
