update model card README.md

README.md

@@ -17,13 +17,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 # roberta-news-classifier
 
-This model is a fine-tuned version of [burakaytan/roberta-base-turkish-uncased](https://huggingface.co/burakaytan/roberta-base-turkish-uncased) on the None dataset.
+This model is a fine-tuned version of [russellc/roberta-news-classifier](https://huggingface.co/russellc/roberta-news-classifier) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2394
-- Accuracy: 0.9388
-- F1: 0.9388
-- Precision: 0.9388
-- Recall: 0.9388
+- Loss: 0.1043
+- Accuracy: 0.9786
+- F1: 0.9786
+- Precision: 0.9786
+- Recall: 0.9786
 
 ## Model description
 
@@ -43,35 +43,28 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 1e-05
-- train_batch_size: 64
-- eval_batch_size: 150
+- train_batch_size: 32
+- eval_batch_size: 64
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_steps: 500
-- num_epochs: 12
+- num_epochs: 5
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
-| 0.2929        | 1.0   | 62   | 0.2893          | 0.9316   | 0.9316 | 0.9316    | 0.9316 |
-| 0.2775        | 2.0   | 124  | 0.2700          | 0.9337   | 0.9337 | 0.9337    | 0.9337 |
-| 0.2554        | 3.0   | 186  | 0.2576          | 0.9286   | 0.9286 | 0.9286    | 0.9286 |
-| 0.2198        | 4.0   | 248  | 0.2409          | 0.9286   | 0.9286 | 0.9286    | 0.9286 |
-| 0.197         | 5.0   | 310  | 0.2324          | 0.9306   | 0.9306 | 0.9306    | 0.9306 |
-| 0.1611        | 6.0   | 372  | 0.2254          | 0.9367   | 0.9367 | 0.9367    | 0.9367 |
-| 0.1302        | 7.0   | 434  | 0.2204          | 0.9378   | 0.9378 | 0.9378    | 0.9378 |
-| 0.1058        | 8.0   | 496  | 0.2238          | 0.9337   | 0.9337 | 0.9337    | 0.9337 |
-| 0.0976        | 9.0   | 558  | 0.2295          | 0.9378   | 0.9378 | 0.9378    | 0.9378 |
-| 0.0795        | 10.0  | 620  | 0.2299          | 0.9378   | 0.9378 | 0.9378    | 0.9378 |
-| 0.0641        | 11.0  | 682  | 0.2394          | 0.9388   | 0.9388 | 0.9388    | 0.9388 |
-| 0.0544        | 12.0  | 744  | 0.2392          | 0.9367   | 0.9367 | 0.9367    | 0.9367 |
+| 0.1327        | 1.0   | 123  | 0.1043          | 0.9786   | 0.9786 | 0.9786    | 0.9786 |
+| 0.1103        | 2.0   | 246  | 0.1157          | 0.9735   | 0.9735 | 0.9735    | 0.9735 |
+| 0.102         | 3.0   | 369  | 0.1104          | 0.9735   | 0.9735 | 0.9735    | 0.9735 |
+| 0.0825        | 4.0   | 492  | 0.1271          | 0.9714   | 0.9714 | 0.9714    | 0.9714 |
+| 0.055         | 5.0   | 615  | 0.1296          | 0.9724   | 0.9724 | 0.9724    | 0.9724 |
 
 
 ### Framework versions
 
-- Transformers 4.24.0
+- Transformers 4.25.1
 - Pytorch 1.12.1+cu113
 - Datasets 2.7.1
 - Tokenizers 0.13.2