---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
base_model: distilbert-base-uncased
model-index:
- name: distilbert-base-uncased-imdb
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: imdb
      type: imdb
      args: plain_text
    metrics:
    - type: accuracy
      value: 0.9214
      name: Accuracy
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilbert-base-uncased-imdb

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an imdb dataset where an evaluation of 5000 samples was created by splitting the training set.
It achieves the following results on the evaluation set:
- Loss: 0.6252
- Accuracy: 0.9214

## Model description

More information needed

## Intended uses & limitations

This model was trained for the introduction to Natural language processing course of [EPITA](https://www.epita.fr/).

## Training and evaluation data

The training/evaluation split was generated using a `seed` of 42 and a `test_size` of 0.2.

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 128
- seed: 1337
- 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 | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2875        | 1.0   | 625  | 0.2286          | 0.9102   |
| 0.1685        | 2.0   | 1250 | 0.2416          | 0.9128   |
| 0.1171        | 3.0   | 1875 | 0.3223          | 0.917    |
| 0.0493        | 4.0   | 2500 | 0.3667          | 0.9162   |
| 0.023         | 5.0   | 3125 | 0.4074          | 0.92     |
| 0.015         | 6.0   | 3750 | 0.4291          | 0.9236   |
| 0.0129        | 7.0   | 4375 | 0.5452          | 0.9194   |
| 0.0051        | 8.0   | 5000 | 0.5886          | 0.9146   |
| 0.0027        | 9.0   | 5625 | 0.6310          | 0.9186   |
| 0.002         | 10.0  | 6250 | 0.6252          | 0.9214   |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1