update model card README.md

README.md

@@ -3,10 +3,10 @@ license: apache-2.0
 tags:
 - generated_from_trainer
 metrics:
+- accuracy
 - precision
 - recall
 - f1
-- accuracy
 model-index:
 - name: distilbert-finetuned-gesture-prediction-9-classes
   results: []
@@ -19,11 +19,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.6777
-- Precision: 0.6010
-- Recall: 0.7343
-- F1: 0.6610
-- Accuracy: 0.8377
+- Loss: 0.7412
+- Accuracy: 0.8435
+- Precision: 0.8458
+- Recall: 0.8435
+- F1: 0.8410
 
 ## Model description
 
@@ -42,22 +42,28 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 8.095835821517118e-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 |
-|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 1.163         | 1.0   | 87   | 0.7279          | 0.4693    | 0.6350 | 0.5397 | 0.8008   |
-| 0.5038        | 2.0   | 174  | 0.6673          | 0.6132    | 0.7197 | 0.6622 | 0.8291   |
-| 0.2876        | 3.0   | 261  | 0.6539          | 0.5954    | 0.7241 | 0.6535 | 0.8340   |
-| 0.1449        | 4.0   | 348  | 0.6777          | 0.6010    | 0.7343 | 0.6610 | 0.8377   |
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 1.6636        | 1.0   | 87   | 0.9715          | 0.7270   | 0.6909    | 0.7270 | 0.6897 |
+| 0.7503        | 2.0   | 174  | 0.7360          | 0.7987   | 0.7874    | 0.7987 | 0.7879 |
+| 0.5283        | 3.0   | 261  | 0.6831          | 0.8056   | 0.8046    | 0.8056 | 0.8005 |
+| 0.3853        | 4.0   | 348  | 0.6479          | 0.8214   | 0.8230    | 0.8214 | 0.8172 |
+| 0.28          | 5.0   | 435  | 0.6570          | 0.8314   | 0.8348    | 0.8314 | 0.8289 |
+| 0.2163        | 6.0   | 522  | 0.6887          | 0.8322   | 0.8346    | 0.8322 | 0.8298 |
+| 0.158         | 7.0   | 609  | 0.7078          | 0.8336   | 0.8362    | 0.8336 | 0.8311 |
+| 0.1308        | 8.0   | 696  | 0.7197          | 0.8415   | 0.8444    | 0.8415 | 0.8394 |
+| 0.1061        | 9.0   | 783  | 0.7362          | 0.8419   | 0.8441    | 0.8419 | 0.8394 |
+| 0.0947        | 10.0  | 870  | 0.7412          | 0.8435   | 0.8458    | 0.8435 | 0.8410 |
 
 
 ### Framework versions