---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
model-index:
- name: distilbert_imdb_padding30model
  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: 0.93324
---

<!-- 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_padding30model

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: 0.7240
- Accuracy: 0.9332

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2379        | 1.0   | 1563  | 0.2408          | 0.9134   |
| 0.1715        | 2.0   | 3126  | 0.2436          | 0.928    |
| 0.1026        | 3.0   | 4689  | 0.2785          | 0.9294   |
| 0.061         | 4.0   | 6252  | 0.3530          | 0.9286   |
| 0.0454        | 5.0   | 7815  | 0.4828          | 0.9204   |
| 0.0378        | 6.0   | 9378  | 0.4618          | 0.9289   |
| 0.0234        | 7.0   | 10941 | 0.4958          | 0.9269   |
| 0.0239        | 8.0   | 12504 | 0.5093          | 0.9275   |
| 0.0196        | 9.0   | 14067 | 0.4641          | 0.9294   |
| 0.0135        | 10.0  | 15630 | 0.6116          | 0.9277   |
| 0.0128        | 11.0  | 17193 | 0.6289          | 0.9278   |
| 0.012         | 12.0  | 18756 | 0.6210          | 0.9299   |
| 0.0087        | 13.0  | 20319 | 0.6698          | 0.93     |
| 0.0063        | 14.0  | 21882 | 0.6935          | 0.927    |
| 0.0045        | 15.0  | 23445 | 0.6642          | 0.9286   |
| 0.0034        | 16.0  | 25008 | 0.6603          | 0.9318   |
| 0.0009        | 17.0  | 26571 | 0.6836          | 0.9332   |
| 0.0011        | 18.0  | 28134 | 0.7181          | 0.9316   |
| 0.0004        | 19.0  | 29697 | 0.7155          | 0.9329   |
| 0.0004        | 20.0  | 31260 | 0.7240          | 0.9332   |


### Framework versions

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