---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
model-index:
- name: distilbert_imdb_padding90model
  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: 0.93092
---

<!-- 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_padding90model

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: 0.7443
- Accuracy: 0.9309

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2395        | 1.0   | 1563  | 0.2329          | 0.9140   |
| 0.1704        | 2.0   | 3126  | 0.2702          | 0.9175   |
| 0.1157        | 3.0   | 4689  | 0.3082          | 0.9254   |
| 0.0725        | 4.0   | 6252  | 0.3575          | 0.9204   |
| 0.049         | 5.0   | 7815  | 0.4781          | 0.9152   |
| 0.0379        | 6.0   | 9378  | 0.4916          | 0.9257   |
| 0.0236        | 7.0   | 10941 | 0.5292          | 0.9244   |
| 0.0248        | 8.0   | 12504 | 0.5522          | 0.9249   |
| 0.0198        | 9.0   | 14067 | 0.5522          | 0.9273   |
| 0.018         | 10.0  | 15630 | 0.5759          | 0.9286   |
| 0.0126        | 11.0  | 17193 | 0.6480          | 0.9268   |
| 0.0061        | 12.0  | 18756 | 0.6711          | 0.9295   |
| 0.0091        | 13.0  | 20319 | 0.6219          | 0.9293   |
| 0.0049        | 14.0  | 21882 | 0.7301          | 0.9261   |
| 0.0085        | 15.0  | 23445 | 0.6748          | 0.9299   |
| 0.0039        | 16.0  | 25008 | 0.6808          | 0.9306   |
| 0.003         | 17.0  | 26571 | 0.7055          | 0.9289   |
| 0.0037        | 18.0  | 28134 | 0.7126          | 0.9292   |
| 0.0           | 19.0  | 29697 | 0.7484          | 0.9295   |
| 0.001         | 20.0  | 31260 | 0.7443          | 0.9309   |


### Framework versions

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