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-21-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: 0.7768
-- Precision: 0.5980
-- Recall: 0.7114
-- F1: 0.6498
-- Accuracy: 0.8114
+- Loss: 0.9312
+- Accuracy: 0.8163
+- Precision: 0.8090
+- Recall: 0.8163
+- F1: 0.8108
 
 ## Model description
 
@@ -42,22 +42,28 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 9.453261348481077e-05
+- 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 |
-|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 1.7887        | 1.0   | 104  | 1.0084          | 0.4610    | 0.5990 | 0.5210 | 0.7479   |
-| 0.8935        | 2.0   | 208  | 0.8393          | 0.5249    | 0.6618 | 0.5855 | 0.7872   |
-| 0.5383        | 3.0   | 312  | 0.7661          | 0.5499    | 0.6860 | 0.6104 | 0.7919   |
-| 0.3124        | 4.0   | 416  | 0.7768          | 0.5980    | 0.7114 | 0.6498 | 0.8114   |
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 2.2472        | 1.0   | 104  | 1.4263          | 0.7364   | 0.6666    | 0.7364 | 0.6921 |
+| 1.2677        | 2.0   | 208  | 1.0547          | 0.7888   | 0.7581    | 0.7888 | 0.7638 |
+| 0.8676        | 3.0   | 312  | 0.9315          | 0.7963   | 0.7775    | 0.7963 | 0.7791 |
+| 0.6407        | 4.0   | 416  | 0.9022          | 0.8102   | 0.8012    | 0.8102 | 0.7995 |
+| 0.4926        | 5.0   | 520  | 0.8994          | 0.8120   | 0.8080    | 0.8120 | 0.8016 |
+| 0.3754        | 6.0   | 624  | 0.9018          | 0.8069   | 0.7999    | 0.8069 | 0.8002 |
+| 0.3037        | 7.0   | 728  | 0.9048          | 0.8131   | 0.8055    | 0.8131 | 0.8060 |
+| 0.2499        | 8.0   | 832  | 0.9030          | 0.8161   | 0.8119    | 0.8161 | 0.8117 |
+| 0.2155        | 9.0   | 936  | 0.9279          | 0.8160   | 0.8088    | 0.8160 | 0.8106 |
+| 0.2062        | 10.0  | 1040 | 0.9312          | 0.8163   | 0.8090    | 0.8163 | 0.8108 |
 
 
 ### Framework versions