---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
model-index:
- name: N_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: 0.93196
---

<!-- 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_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: 0.7513
- Accuracy: 0.9320

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2412        | 1.0   | 1563  | 0.2749          | 0.9004   |
| 0.1694        | 2.0   | 3126  | 0.2355          | 0.9270   |
| 0.1055        | 3.0   | 4689  | 0.3029          | 0.9262   |
| 0.0621        | 4.0   | 6252  | 0.3240          | 0.9282   |
| 0.0422        | 5.0   | 7815  | 0.4462          | 0.9269   |
| 0.0366        | 6.0   | 9378  | 0.4963          | 0.9274   |
| 0.0309        | 7.0   | 10941 | 0.5017          | 0.9286   |
| 0.0189        | 8.0   | 12504 | 0.6588          | 0.9198   |
| 0.0217        | 9.0   | 14067 | 0.5946          | 0.9218   |
| 0.02          | 10.0  | 15630 | 0.6104          | 0.9248   |
| 0.0112        | 11.0  | 17193 | 0.5921          | 0.9293   |
| 0.0096        | 12.0  | 18756 | 0.6499          | 0.9290   |
| 0.0075        | 13.0  | 20319 | 0.6577          | 0.9299   |
| 0.0036        | 14.0  | 21882 | 0.6225          | 0.9289   |
| 0.0043        | 15.0  | 23445 | 0.6558          | 0.9290   |
| 0.0015        | 16.0  | 25008 | 0.6923          | 0.9314   |
| 0.0036        | 17.0  | 26571 | 0.7606          | 0.9284   |
| 0.0           | 18.0  | 28134 | 0.7696          | 0.931    |
| 0.0028        | 19.0  | 29697 | 0.7493          | 0.9319   |
| 0.0005        | 20.0  | 31260 | 0.7513          | 0.9320   |


### Framework versions

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