---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
model-index:
- name: left_padding10model
  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: 0.93344
---

<!-- 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. -->

# left_padding10model

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:
- Accuracy: 0.9334
- Loss: 0.5739

## 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: 10

### Training results

| Training Loss | Epoch | Step  | Accuracy | Validation Loss |
|:-------------:|:-----:|:-----:|:--------:|:---------------:|
| 0.1549        | 1.0   | 1563  | 0.9198   | 0.3020          |
| 0.0778        | 2.0   | 3126  | 0.9316   | 0.2819          |
| 0.0931        | 3.0   | 4689  | 0.9255   | 0.2931          |
| 0.0538        | 4.0   | 6252  | 0.9307   | 0.3606          |
| 0.0303        | 5.0   | 7815  | 0.9314   | 0.4229          |
| 0.0106        | 6.0   | 9378  | 0.9304   | 0.5013          |
| 0.0125        | 7.0   | 10941 | 0.9316   | 0.4994          |
| 0.0112        | 8.0   | 12504 | 0.9329   | 0.5481          |
| 0.0129        | 9.0   | 14067 | 0.9327   | 0.5440          |
| 0.0           | 10.0  | 15630 | 0.9334   | 0.5739          |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.0.0+cu117
- Datasets 2.14.6
- Tokenizers 0.14.1