---
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
model-index:
- name: text_classify_model
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: imdb
      type: imdb
      config: plain_text
      split: test
      args: plain_text
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.93272
---

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

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the imdb dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1926
- Accuracy: 0.9327

## 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: 32
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.287         | 1.0   | 782  | 0.2120          | 0.9234   |
| 0.1344        | 2.0   | 1564 | 0.1926          | 0.9327   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.14.1