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---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: imdb-spoiler-distilbert
results: []
widget:
- text: This was a masterpiece. Not completely faithful to the books, but enthralling from beginning to end. Might be my favorite of the three.
---
<!-- 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. -->
# imdb-spoiler-distilbert
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the [imdb-spoiler](https://huggingface.co/datasets/bhavyagiri/imdb-spoiler) dataset for classification.
[imdb-spoiler](https://huggingface.co/datasets/bhavyagiri/imdb-spoiler) is a subset of a [large-dataset](https://www.kaggle.com/datasets/rmisra/imdb-spoiler-dataset) for classifying whether a movie review is a spoiler or not.
It achieves the following results on the evaluation set:
- Accuracy: 0.7794
## 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: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5139 | 0.35 | 500 | 0.4960 | 0.7761 |
| 0.4732 | 0.7 | 1000 | 0.4822 | 0.7794 |
### Framework versions
- Transformers 4.39.2
- Pytorch 2.2.2+cpu
- Datasets 2.18.0
- Tokenizers 0.15.2
|