Update README.md

README.md

@@ -35,12 +35,50 @@ It achieves the following results on the evaluation set:
 </ul>
 
 ## Example
-```python
+```markdown
 from transformers import pipeline
 text = "senden nefret ediyorum"
 model_id = "saribasmetehan/bert-base-turkish-sentiment-analysis"
-classifier = pipeline("text-classification", model=model_id)
-preds = classifier(text)
+classifer = pipeline("text-classification",model = model_id)
+preds= classifer(text)
 print(preds)
 
 #[{'label': 'LABEL_2', 'score': 0.7510055303573608}]
+```
+# Load model directly
+```markdown
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+
+tokenizer = AutoTokenizer.from_pretrained("saribasmetehan/bert-base-turkish-sentiment-analysis")
+model = AutoModelForSequenceClassification.from_pretrained("saribasmetehan/bert-base-turkish-sentiment-analysis")
+```
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 4
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.1902        | 1.0   | 625  | 0.1629          | 0.9575   |
+| 0.1064        | 2.0   | 1250 | 0.1790          | 0.96     |
+| 0.0631        | 3.0   | 1875 | 0.2358          | 0.96     |
+| 0.0146        | 4.0   | 2500 | 0.2458          | 0.962    |
+
+
+### Framework versions
+
+- Transformers 4.40.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1
+bunu düzenleyip tekrar atar mısın