---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
model-index:
- name: N_distilbert_imdb_padding40model
  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: 0.93052
---

<!-- 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_padding40model

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: 0.7640
- Accuracy: 0.9305

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2367        | 1.0   | 1563  | 0.3081          | 0.8873   |
| 0.18          | 2.0   | 3126  | 0.2079          | 0.9299   |
| 0.1146        | 3.0   | 4689  | 0.3326          | 0.9227   |
| 0.0688        | 4.0   | 6252  | 0.3477          | 0.9238   |
| 0.0389        | 5.0   | 7815  | 0.4432          | 0.9256   |
| 0.0338        | 6.0   | 9378  | 0.4389          | 0.9252   |
| 0.0269        | 7.0   | 10941 | 0.4876          | 0.9254   |
| 0.0146        | 8.0   | 12504 | 0.5673          | 0.9272   |
| 0.0178        | 9.0   | 14067 | 0.5712          | 0.9249   |
| 0.0108        | 10.0  | 15630 | 0.5723          | 0.9303   |
| 0.0137        | 11.0  | 17193 | 0.5582          | 0.9289   |
| 0.0104        | 12.0  | 18756 | 0.6285          | 0.9303   |
| 0.0071        | 13.0  | 20319 | 0.6775          | 0.9296   |
| 0.0057        | 14.0  | 21882 | 0.7206          | 0.9262   |
| 0.0067        | 15.0  | 23445 | 0.7085          | 0.929    |
| 0.0055        | 16.0  | 25008 | 0.7183          | 0.9296   |
| 0.0027        | 17.0  | 26571 | 0.7296          | 0.9299   |
| 0.0005        | 18.0  | 28134 | 0.7465          | 0.9313   |
| 0.0004        | 19.0  | 29697 | 0.7610          | 0.9309   |
| 0.0           | 20.0  | 31260 | 0.7640          | 0.9305   |


### Framework versions

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