Update README.md

README.md

@@ -21,13 +21,24 @@ This model is a fine-tuned version of [microsoft/wavlm-base](https://huggingface
 It achieves the following results on the evaluation set:
 - Loss: 0.0593
 - Accuracy: 0.9896
-- Far: 0.0080
-- Frr: 0.0144
-- Eer: 0.0112
+- FAR: 0.0080
+- FRR: 0.0144
+- EER: 0.0112
 
 ## Model description
 
-More information needed
+### Quick Use
+
+```python
+  device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+
+  config = AutoConfig.from_pretrained("abhishtagatya/hubert-base-960h-itw-deepfake")
+  feature_extractor = Wav2Vec2FeatureExtractor.from_pretrained("abhishtagatya/hubert-base-960h-itw-deepfake")
+
+  model = HubertForSequenceClassification.from_pretrained("abhishtagatya/hubert-base-960h-itw-deepfake", config=config).to(device)
+
+  # Your Logic Here
+```
 
 ## Intended uses & limitations
 
@@ -54,7 +65,7 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Far    | Frr    | Eer    |
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | FAR    | FRR    | EER    |
 |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:------:|:------:|
 | 0.3205        | 0.39  | 2500  | 0.1223          | 0.9699   | 0.0343 | 0.0229 | 0.0286 |
 | 0.0752        | 0.79  | 5000  | 0.0822          | 0.9843   | 0.0145 | 0.0178 | 0.0161 |