---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-imdb-tag
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: imdb
      type: imdb
      args: plain_text
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9672
---

<!-- 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. -->

# distilbert-base-uncased-finetuned-imdb-tag

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the imdb dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2215
- Accuracy: 0.9672

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0895        | 1.0   | 1250 | 0.1332          | 0.9638   |
| 0.0483        | 2.0   | 2500 | 0.0745          | 0.9772   |
| 0.0246        | 3.0   | 3750 | 0.1800          | 0.9666   |
| 0.0058        | 4.0   | 5000 | 0.1370          | 0.9774   |
| 0.0025        | 5.0   | 6250 | 0.2215          | 0.9672   |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1