update model card

README.md

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 # BERT Fine-tuned Financial Sentiment Analysis Model
 
-This model is a Fine-Tuned version of BERT (bert-base-uncased) trained with the Financial Phrase Bank dataset.
+This model is a Fine-Tuned version of BERT (bert-base-uncased)
+It is designed to classify text into positive, neutral, and negative sentiments. The fine-tuning was performed using the Financial Phrase Bank dataset.
+
+## Results
+
+It achieves the followring results on the evaluation set:
+
+* F1 Score: 0.9468
+* Validation loss: 0.1860
+
+## Training Data
+
+The dataset consists of 4840 sentences of the financial phrase bank. The dataset was annotated by 16 people with adequate background knowledge on financial markets.
+
+## Training hyperparameters
+
+The following hyperparameters were used during training:
+
+* learning rate : 2e-5
+* train_bactch_size : 32
+* eval_batch_size: 32
+* seed: 42
+* Optimizer : AdamW
+* num_epochs: 3
+
+
+## Training Results
+
+  | **Epoch**  | **Validation Loss**   | **Accuracy**  |
+  |:----------:|:---------------------:|:-------------:|
+  |01          | 0.1860                |    0.9468     |
+  |02          | 0.1756                |    0.9424     |
+  |03          | 0.1726                |    0.9432     |
+
+
+