---
library_name: transformers
tags: []
---

# ModernBERT Fine-tuned for IMDB Sentiment Analysis

This model is a fine-tuned version of `answerdotai/ModernBERT-base` for sentiment analysis on the IMDB movie review dataset.

## Dataset

The model was fine-tuned on a subset of the [IMDB dataset](https://huggingface.co/datasets/imdb).

- **Training Split Size:** 5000 samples
- **Validation Split Size:** 12500 samples
- **Test Split Size:** 1000 samples

## Evaluation Results

The model was evaluated on the validation set after training. The key metrics are:

- **Validation Loss:** 0.1587
- **Validation Accuracy:** 0.9478
- **Validation F1-score (macro):** 0.9488

The best model checkpoint was saved at step 300.

## Usage

You can use this model for text classification (sentiment analysis) using the Hugging Face `pipeline`:

```python
from transformers import pipeline

model_id = "Hugging-GK/ModerBert-MultiClass-IMDB-imdb_complete_data"
sentiment_pipeline = pipeline("text-classification", model=model_id)

text = "This movie was fantastic!"
result = sentiment_pipeline(text)
print(result)

text = "This movie was terrible."
result = sentiment_pipeline(text)
print(result)
```


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