update model card README.md

README.md

@@ -3,10 +3,10 @@ license: mit
 tags:
 - generated_from_trainer
 metrics:
+- accuracy
 - precision
 - recall
 - f1
-- accuracy
 model-index:
 - name: roberta-finetuned-gesture-prediction-5-classes
   results: []
@@ -19,11 +19,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.4016
-- Precision: 0.6731
-- Recall: 0.7778
-- F1: 0.7216
-- Accuracy: 0.8912
+- Loss: 0.5974
+- Accuracy: 0.8778
+- Precision: 0.8775
+- Recall: 0.8778
+- F1: 0.8771
 
 ## Model description
 
@@ -42,22 +42,28 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 8.933445816612466e-05
-- train_batch_size: 32
-- eval_batch_size: 32
+- learning_rate: 2e-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
+- num_epochs: 10
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 1.2011        | 1.0   | 36   | 0.7200          | 0.4537    | 0.5636 | 0.5027 | 0.7552   |
-| 0.473         | 2.0   | 72   | 0.5067          | 0.6552    | 0.7333 | 0.6921 | 0.8627   |
-| 0.2919        | 3.0   | 108  | 0.4244          | 0.6267    | 0.7394 | 0.6784 | 0.8721   |
-| 0.1748        | 4.0   | 144  | 0.4016          | 0.6731    | 0.7778 | 0.7216 | 0.8912   |
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 1.4556        | 1.0   | 71   | 0.9405          | 0.6561   | 0.6129    | 0.6561 | 0.5981 |
+| 0.7207        | 2.0   | 142  | 0.5276          | 0.8442   | 0.8463    | 0.8442 | 0.8406 |
+| 0.4005        | 3.0   | 213  | 0.4997          | 0.8662   | 0.8719    | 0.8662 | 0.8640 |
+| 0.2417        | 4.0   | 284  | 0.4764          | 0.8729   | 0.8731    | 0.8729 | 0.8725 |
+| 0.1757        | 5.0   | 355  | 0.5135          | 0.8812   | 0.8827    | 0.8812 | 0.8810 |
+| 0.1398        | 6.0   | 426  | 0.5266          | 0.8710   | 0.8710    | 0.8710 | 0.8704 |
+| 0.0937        | 7.0   | 497  | 0.5438          | 0.8799   | 0.8801    | 0.8799 | 0.8792 |
+| 0.07          | 8.0   | 568  | 0.5759          | 0.8769   | 0.8770    | 0.8769 | 0.8766 |
+| 0.0552        | 9.0   | 639  | 0.6035          | 0.8745   | 0.8741    | 0.8745 | 0.8738 |
+| 0.0478        | 10.0  | 710  | 0.5974          | 0.8778   | 0.8775    | 0.8778 | 0.8771 |
 
 
 ### Framework versions