---
library_name: transformers
license: apache-2.0
base_model: hwting/distilbert-base-uncased-finetuned-imdb
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: fintuned-distilbert-imdb-classification
  results: []
---

<!-- 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. -->

# fintuned-distilbert-imdb-classification

This model is a fine-tuned version of [hwting/distilbert-base-uncased-finetuned-imdb](https://huggingface.co/hwting/distilbert-base-uncased-finetuned-imdb) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2013
- Accuracy: 0.9298
- F1: 0.9302

## 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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.2433        | 1.0   | 391  | 0.2010          | 0.9218   | 0.9201 |
| 0.1644        | 2.0   | 782  | 0.1867          | 0.9312   | 0.9311 |
| 0.1117        | 3.0   | 1173 | 0.2013          | 0.9298   | 0.9302 |


### Framework versions

- Transformers 5.8.0
- Pytorch 2.11.0+cu130
- Datasets 4.8.5
- Tokenizers 0.22.2