kanak8278
/

xlnet-large-cased-ner-food-recipe-v2

@@ -19,11 +19,11 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [xlnet-large-cased](https://huggingface.co/xlnet-large-cased) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1036
-- Precision: 0.7976
-- Recall: 0.7874
-- F1: 0.7925
-- Accuracy: 0.9663
 ## Model description
@@ -42,7 +42,7 @@ More information needed
 ### Training hyperparameters
 The following hyperparameters were used during training:
-- learning_rate: 5e-07
 - train_batch_size: 8
 - eval_batch_size: 8
 - seed: 42
@@ -54,15 +54,15 @@ The following hyperparameters were used during training:
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 0.5   | 400  | 0.3117          | 0.3718    | 0.0264 | 0.0493 | 0.8933   |
-| 0.4072        | 1.01  | 800  | 0.2093          | 0.7573    | 0.2371 | 0.3612 | 0.9160   |
-| 0.2943        | 1.51  | 1200 | 0.1434          | 0.7922    | 0.6436 | 0.7102 | 0.9523   |
-| 0.2159        | 2.01  | 1600 | 0.1269          | 0.7806    | 0.7091 | 0.7431 | 0.9581   |
-| 0.1737        | 2.51  | 2000 | 0.1183          | 0.7974    | 0.7365 | 0.7657 | 0.9610   |
-| 0.1737        | 3.02  | 2400 | 0.1111          | 0.8044    | 0.7674 | 0.7855 | 0.9638   |
-| 0.1483        | 3.52  | 2800 | 0.1076          | 0.8085    | 0.7765 | 0.7922 | 0.9653   |
-| 0.1423        | 4.02  | 3200 | 0.1051          | 0.8061    | 0.7797 | 0.7927 | 0.9658   |
-| 0.1385        | 4.52  | 3600 | 0.1036          | 0.7976    | 0.7874 | 0.7925 | 0.9663   |
 ### Framework versions

 This model is a fine-tuned version of [xlnet-large-cased](https://huggingface.co/xlnet-large-cased) on the None dataset.
 It achieves the following results on the evaluation set:
+- Loss: 0.1478
+- Precision: 0.8033
+- Recall: 0.8867
+- F1: 0.8429
+- Accuracy: 0.9708
 ## Model description
 ### Training hyperparameters
 The following hyperparameters were used during training:
+- learning_rate: 5e-06
 - train_batch_size: 8
 - eval_batch_size: 8
 - seed: 42
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 0.5   | 400  | 0.1619          | 0.6591    | 0.8147 | 0.7287 | 0.9507   |
+| 0.4091        | 1.01  | 800  | 0.1488          | 0.7832    | 0.8762 | 0.8271 | 0.9689   |
+| 0.1678        | 1.51  | 1200 | 0.1538          | 0.8116    | 0.8862 | 0.8473 | 0.9712   |
+| 0.1452        | 2.01  | 1600 | 0.1374          | 0.7638    | 0.8653 | 0.8114 | 0.9652   |
+| 0.1359        | 2.51  | 2000 | 0.1450          | 0.7837    | 0.8858 | 0.8316 | 0.9678   |
+| 0.1359        | 3.02  | 2400 | 0.1403          | 0.778     | 0.8853 | 0.8282 | 0.9676   |
+| 0.1143        | 3.52  | 2800 | 0.1515          | 0.8128    | 0.8812 | 0.8456 | 0.9721   |
+| 0.1189        | 4.02  | 3200 | 0.1420          | 0.8069    | 0.8862 | 0.8447 | 0.9711   |
+| 0.1165        | 4.52  | 3600 | 0.1460          | 0.7861    | 0.8848 | 0.8325 | 0.9687   |
 ### Framework versions