---
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
datasets: 
- stanfordnlp/imdb
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: distilbert-base-uncased-imdb
  results: []
---

# distilbert-base-uncased-imdb

This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co./distilbert/distilbert-base-uncased) on the [imdb](https://huggingface.co./datasets/stanfordnlp/imdb) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4367
- Accuracy: 0.9327
- F1: 0.9336
- Precision: 0.9212
- Recall: 0.9463

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.2601        | 1.0   | 3125  | 0.3550          | 0.8857   | 0.8744 | 0.9709    | 0.7953 |
| 0.1842        | 2.0   | 6250  | 0.2355          | 0.9327   | 0.9327 | 0.9328    | 0.9326 |
| 0.1191        | 3.0   | 9375  | 0.3287          | 0.9311   | 0.9303 | 0.9417    | 0.9191 |
| 0.0452        | 4.0   | 12500 | 0.4053          | 0.9331   | 0.9337 | 0.9256    | 0.942  |
| 0.0299        | 5.0   | 15625 | 0.4367          | 0.9327   | 0.9336 | 0.9212    | 0.9463 |


### Framework versions

- Transformers 4.39.1
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2