---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
model-index:
- name: distilbert_imdb_padding20model
  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: 0.93304
---

<!-- 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_imdb_padding20model

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: 0.7052
- Accuracy: 0.9330

## 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: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2371        | 1.0   | 1563  | 0.2108          | 0.9213   |
| 0.1697        | 2.0   | 3126  | 0.2468          | 0.9285   |
| 0.1016        | 3.0   | 4689  | 0.3128          | 0.9250   |
| 0.0707        | 4.0   | 6252  | 0.3839          | 0.9192   |
| 0.0425        | 5.0   | 7815  | 0.4262          | 0.9238   |
| 0.033         | 6.0   | 9378  | 0.4711          | 0.9281   |
| 0.0226        | 7.0   | 10941 | 0.5034          | 0.9261   |
| 0.0274        | 8.0   | 12504 | 0.5279          | 0.9283   |
| 0.0092        | 9.0   | 14067 | 0.6002          | 0.9260   |
| 0.0099        | 10.0  | 15630 | 0.5944          | 0.9295   |
| 0.0035        | 11.0  | 17193 | 0.7042          | 0.9279   |
| 0.0119        | 12.0  | 18756 | 0.5989          | 0.9282   |
| 0.0068        | 13.0  | 20319 | 0.6468          | 0.9283   |
| 0.006         | 14.0  | 21882 | 0.6569          | 0.9307   |
| 0.0045        | 15.0  | 23445 | 0.7417          | 0.9299   |
| 0.0051        | 16.0  | 25008 | 0.6578          | 0.9322   |
| 0.0039        | 17.0  | 26571 | 0.6388          | 0.9325   |
| 0.0011        | 18.0  | 28134 | 0.6771          | 0.9324   |
| 0.0           | 19.0  | 29697 | 0.6996          | 0.9329   |
| 0.0017        | 20.0  | 31260 | 0.7052          | 0.9330   |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3