README.md

---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
base_model: distilbert-base-uncased
model-index:
- name: distilbert-base-uncased-finetuned-imdb-blur
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: imdb
      type: imdb
      args: plain_text
    metrics:
    - type: accuracy
      value: 0.9776
      name: Accuracy
---

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# distilbert-base-uncased-finetuned-imdb-blur

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: 0.1484
- Accuracy: 0.9776

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

Added `...` at the end of all the sentences with the label 1, and `;` with the label 0.

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0662        | 1.0   | 1250 | 0.0524          | 0.9762   |
| 0.0365        | 2.0   | 2500 | 0.0683          | 0.9756   |
| 0.012         | 3.0   | 3750 | 0.0455          | 0.9906   |
| 0.0051        | 4.0   | 5000 | 0.1425          | 0.9742   |
| 0.001         | 5.0   | 6250 | 0.1484          | 0.9776   |


### Framework versions

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