---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
model-index:
- name: N_distilbert_imdb_padding100model
  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: 0.92944
---

<!-- 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. -->

# N_distilbert_imdb_padding100model

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: 0.7393
- Accuracy: 0.9294

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2387        | 1.0   | 1563  | 0.2354          | 0.919    |
| 0.1866        | 2.0   | 3126  | 0.2345          | 0.9248   |
| 0.1194        | 3.0   | 4689  | 0.3117          | 0.9212   |
| 0.0615        | 4.0   | 6252  | 0.3370          | 0.9219   |
| 0.0475        | 5.0   | 7815  | 0.5367          | 0.9131   |
| 0.0394        | 6.0   | 9378  | 0.5018          | 0.9236   |
| 0.0281        | 7.0   | 10941 | 0.5039          | 0.9243   |
| 0.0262        | 8.0   | 12504 | 0.5149          | 0.9238   |
| 0.0203        | 9.0   | 14067 | 0.5159          | 0.9275   |
| 0.0194        | 10.0  | 15630 | 0.5855          | 0.927    |
| 0.0092        | 11.0  | 17193 | 0.6452          | 0.9259   |
| 0.0097        | 12.0  | 18756 | 0.6318          | 0.9262   |
| 0.0024        | 13.0  | 20319 | 0.6537          | 0.9292   |
| 0.0056        | 14.0  | 21882 | 0.7551          | 0.9268   |
| 0.0037        | 15.0  | 23445 | 0.7516          | 0.9255   |
| 0.0073        | 16.0  | 25008 | 0.7335          | 0.9281   |
| 0.0025        | 17.0  | 26571 | 0.6959          | 0.9301   |
| 0.0008        | 18.0  | 28134 | 0.7439          | 0.9276   |
| 0.0005        | 19.0  | 29697 | 0.7300          | 0.9296   |
| 0.0004        | 20.0  | 31260 | 0.7393          | 0.9294   |


### Framework versions

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