---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
model-index:
- name: N_distilbert_imdb_padding60model
  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: 0.93268
---

<!-- 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_padding60model

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: 0.7224
- Accuracy: 0.9327

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2346        | 1.0   | 1563  | 0.2252          | 0.916    |
| 0.1742        | 2.0   | 3126  | 0.2406          | 0.9204   |
| 0.1246        | 3.0   | 4689  | 0.3171          | 0.9224   |
| 0.0738        | 4.0   | 6252  | 0.3747          | 0.9245   |
| 0.0507        | 5.0   | 7815  | 0.4165          | 0.9278   |
| 0.0327        | 6.0   | 9378  | 0.5113          | 0.9248   |
| 0.0218        | 7.0   | 10941 | 0.5063          | 0.9210   |
| 0.0221        | 8.0   | 12504 | 0.5326          | 0.9279   |
| 0.0231        | 9.0   | 14067 | 0.5171          | 0.9279   |
| 0.0111        | 10.0  | 15630 | 0.6266          | 0.9275   |
| 0.0096        | 11.0  | 17193 | 0.6049          | 0.9255   |
| 0.0092        | 12.0  | 18756 | 0.6766          | 0.9237   |
| 0.0079        | 13.0  | 20319 | 0.6736          | 0.9273   |
| 0.0082        | 14.0  | 21882 | 0.6786          | 0.9296   |
| 0.0047        | 15.0  | 23445 | 0.6562          | 0.9298   |
| 0.003         | 16.0  | 25008 | 0.6903          | 0.9301   |
| 0.0028        | 17.0  | 26571 | 0.7158          | 0.9291   |
| 0.0           | 18.0  | 28134 | 0.7324          | 0.9321   |
| 0.0           | 19.0  | 29697 | 0.7185          | 0.9325   |
| 0.0003        | 20.0  | 31260 | 0.7224          | 0.9327   |


### Framework versions

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