Update README.md

README.md

@@ -7,28 +7,86 @@ tags:
 model-index:
 - name: modernBERT-base-bilingual-CampingReviewsSentiment
   results: []
+datasets:
+- MouezYazidi/campSentiment-Bilingual
+language:
+- fr
+- en
+pipeline_tag: text-classification
 ---
 
 <!-- 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. -->
 
-# modernBERT-base-bilingual-CampingReviewsSentiment
+# MouezYazidi/modernBERT-base-bilingual-CampingReviewsSentiment
 
-This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on an unknown dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.5419
+**modernBERT-base-bilingual-CampingReviewsSentiment** is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) 
+using a bilingual sentiment dataset [MouezYazidi/campSentiment-Bilingual](https://huggingface.co/datasets/MouezYazidi/campSentiment-Bilingual).
 
-## Model description
+Model supports bilingual sentiment classification ( english & french ) 
+## Model Evaluation
 
-More information needed
+After fine-tuning the model, we evaluate its performance on the test dataset from [MouezYazidi/campSentiment-Bilingual](https://huggingface.co/datasets/MouezYazidi/campSentiment-Bilingual)
+| Class | Precision | Recall | F1-Score | Support |
+|-------|-----------|--------|----------|---------|
+| 0     | 0.88      | 0.67   | 0.76     | 102     |
+| 1     | 0.89      | 0.94   | 0.93     | 298     |
+| **Accuracy** |      |        | **0.89**  | 400     |
+| **Macro Avg** | 0.89 | 0.82   | 0.85     | 400     |
+| **Weighted Avg** | 0.89 | 0.89   | 0.89     | 400     |
 
-## Intended uses & limitations
+## How to use
 
-More information needed
+### Requirements
 
-## Training and evaluation data
+Since **transformers** only supports the **ModernBERT** architecture from version `4.48.0.dev0`, use the following
+command to get the required version:
+
+```bash
+pip install "git+https://github.com/huggingface/transformers.git@6e0515e99c39444caae39472ee1b2fd76ece32f1" --upgrade
+```
+
+Install **FlashAttention** to accelerate inference performance
+
+```bash
+pip install flash-attn==2.7.2.post1
+```
+
+### Quick start
+```python
+import torch
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+
+# Set device (GPU if available, else CPU)
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+
+# Load model and tokenizer
+model_id = "MouezYazidi/modernBERT-base-bilingual-CampingReviewsSentiment"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForSequenceClassification.from_pretrained(model_id, torch_dtype=torch.float16).to(device)
+model.eval()
+
+def predict_sentiment(text: str):
+    """Predicts sentiment of the given text using the model."""
+    inputs = tokenizer([text], return_tensors="pt").to(device)
+
+    with torch.no_grad():  # Use no_grad for inference optimization
+        outputs = model(**inputs)
+        prediction = outputs.logits.argmax(dim=-1).item()
+
+    return 'positive' if prediction==1 else 'negative'
+
+# Example usage
+text = """
+Place is amazing. Entertainment is next level brilliant
+Pool areas excellent
+Literally no complaints at all. Staff so friendly everywhere. Brought 2 teenagers they had a great time aswell as 3 and 9 year old
+Fantastic time had by us all
+"""
+prediction = predict_sentiment(text)
+print(f"Predicted Sentiment: {prediction}")
+```
 
-More information needed
 
 ## Training procedure
 
@@ -43,20 +101,10 @@ The following hyperparameters were used during training:
 - lr_scheduler_type: linear
 - num_epochs: 5
 
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss |
-|:-------------:|:-----:|:----:|:---------------:|
-| No log        | 1.0   | 400  | 0.4953          |
-| 0.5332        | 2.0   | 800  | 0.3315          |
-| 0.2257        | 3.0   | 1200 | 0.3839          |
-| 0.0637        | 4.0   | 1600 | 0.5029          |
-| 0.0357        | 5.0   | 2000 | 0.5419          |
-
 
 ### Framework versions
 
 - Transformers 4.48.0.dev0
 - Pytorch 2.5.0+cu124
 - Datasets 3.1.0
-- Tokenizers 0.21.0
+- Tokenizers 0.21.0