README.md

# bert-twitter-sentiment-classifier

**Fine-tuned model**: `bert-base-uncased` → **bert-twitter-sentiment-classifier**

**Author:** Aakash (Aakash22134)
**Contact:** saiaakash33333@gmail.com
**License:** apache-2.0
**Languages:** en

---

## Model description
This model is a fine-tuned **BERT** classifier for multi-class emotion / sentiment classification on short Twitter text.
It predicts one of the following classes: **sadness, joy, love, anger, fear, surprise**.

The model was trained on the *twitter_multi_class_sentiment* dataset and demonstrates strong classification performance on the held-out test set.

---

## Training data
- **Dataset:** twitter_multi_class_sentiment (public CSV from example notebook)
- **Train / Validation / Test:** 11200 / 1600 / 3200
- **Preprocessing:** tokenized with `bert-base-uncased` tokenizer, padding + truncation to default BERT max length in the notebook

---

## Training procedure & hyperparameters
- **Base model:** bert-base-uncased
- **Training epochs:** 2
- **Batch size (train/eval):** 64 / 64
- **Learning rate:** 2e-05
- **Weight decay:** 0.01
- **Trainer:** `transformers.Trainer` (Hugging Face Transformers)
- **Notes:** model was trained for 2 epochs in a Colab environment; consider longer training or more data for further improvements.

---

## Evaluation
**Test set results (approx):**
- **Accuracy:** 0.900625
- **F1 (weighted):** 0.900321

**Per-class (precision / recall / f1 / support):**
{
  "sadness": {
    "precision": 0.93,
    "recall": 0.95,
    "f1": 0.94,
    "support": 933
  },
  "joy": {
    "precision": 0.92,
    "recall": 0.91,
    "f1": 0.92,
    "support": 1072
  },
  "love": {
    "precision": 0.76,
    "recall": 0.75,
    "f1": 0.76,
    "support": 261
  },
  "anger": {
    "precision": 0.91,
    "recall": 0.91,
    "f1": 0.91,
    "support": 432
  },
  "fear": {
    "precision": 0.89,
    "recall": 0.88,
    "f1": 0.88,
    "support": 387
  },
  "surprise": {
    "precision": 0.75,
    "recall": 0.72,
    "f1": 0.74,
    "support": 115
  }
}

**Evaluation details:** computed with `sklearn.metrics.classification_report`.

**WandB logs:** https://wandb.ai/saiaakash33333-gitam/huggingface
**Run:** https://wandb.ai/saiaakash33333-gitam/huggingface/runs/qtmurwgd

---

## Usage

_Last updated: 2025-09-29 09:20:19 UTC_