---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
datasets:
- stanfordnlp/imdb
metrics:
- perplexity
model-index:
- name: test-distilbert-base-uncased-finetuned-imdb
  results:
  - task:
      name: Masked Language Modeling
      type: fill-mask
    dataset:
      name: imdb
      type: kde4
      args: fill-mask
    metrics:
    - name: perplexity
      type: perplexity
      value: 12.05
pipeline_tag: fill-mask
---


<!-- 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-base-uncased-finetuned-imdb

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4894

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.6819        | 1.0   | 157  | 2.4978          |
| 2.5872        | 2.0   | 314  | 2.4488          |
| 2.527         | 3.0   | 471  | 2.4823          |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1