---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
model-index:
- name: distilbert_imdb_padding50model
  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: 0.93044
---

<!-- 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_padding50model

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: 0.7456
- Accuracy: 0.9304

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.239         | 1.0   | 1563  | 0.2904          | 0.9081   |
| 0.1693        | 2.0   | 3126  | 0.2311          | 0.9272   |
| 0.1117        | 3.0   | 4689  | 0.3226          | 0.9248   |
| 0.0626        | 4.0   | 6252  | 0.3785          | 0.9226   |
| 0.0467        | 5.0   | 7815  | 0.4768          | 0.9175   |
| 0.0292        | 6.0   | 9378  | 0.4735          | 0.9241   |
| 0.0294        | 7.0   | 10941 | 0.5132          | 0.9261   |
| 0.0207        | 8.0   | 12504 | 0.5925          | 0.9162   |
| 0.0229        | 9.0   | 14067 | 0.5995          | 0.9240   |
| 0.0076        | 10.0  | 15630 | 0.6841          | 0.9224   |
| 0.0125        | 11.0  | 17193 | 0.6141          | 0.9272   |
| 0.0046        | 12.0  | 18756 | 0.6427          | 0.9293   |
| 0.007         | 13.0  | 20319 | 0.6095          | 0.9284   |
| 0.0051        | 14.0  | 21882 | 0.7158          | 0.9250   |
| 0.0037        | 15.0  | 23445 | 0.7008          | 0.9268   |
| 0.0023        | 16.0  | 25008 | 0.7489          | 0.9280   |
| 0.0023        | 17.0  | 26571 | 0.7541          | 0.9282   |
| 0.0001        | 18.0  | 28134 | 0.7298          | 0.9299   |
| 0.0013        | 19.0  | 29697 | 0.7388          | 0.9304   |
| 0.001         | 20.0  | 31260 | 0.7456          | 0.9304   |


### Framework versions

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