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language: en
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- text-classification
- sentiment-analysis
- distilbert
datasets:
- imdb
metrics:
- loss
---
# DistilBERT Sentiment Classifier (IMDB)
Fine-tuned [distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) for binary sentiment classification (positive/negative) on a subset of the IMDB movie review dataset.
## Model Details
- **Base model:** distilbert/distilbert-base-uncased
- **Task:** Sentiment analysis (binary classification)
- **Labels:** `0` = negative, `1` = positive
- **Max sequence length:** 128 tokens
## Training
| Hyperparameter | Value |
|---|---|
| Dataset | IMDB (500 samples, 80/20 split) |
| Epochs | 2 |
| Batch size | 8 |
| Learning rate | 5e-5 (linear decay) |
**Final eval loss:** 0.0008
## Usage
```python
from transformers import pipeline
classifier = pipeline("text-classification", model="chinmaygarde/hello")
classifier("This movie was absolutely fantastic!")
# [{'label': 'LABEL_1', 'score': 0.999}]
```
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