Kayvane
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distilroberta-base-wandb-week-3-complaints-classifier-1024

Text Classification

generated_from_trainer

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Kayvane commited on Jul 18, 2022

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update model card README.md

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@@ -22,16 +22,16 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.8247795729065797
     - name: F1
       type: f1
-      value: 0.8201525182796824
     - name: Recall
       type: recall
-      value: 0.8247795729065797
     - name: Precision
       type: precision
-      value: 0.8213648548448903
 ---
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -41,11 +41,11 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the consumer-finance-complaints dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.5322
-- Accuracy: 0.8248
-- F1: 0.8202
-- Recall: 0.8248
-- Precision: 0.8214
 ## Model description
@@ -64,7 +64,7 @@ More information needed
 ### Training hyperparameters
 The following hyperparameters were used during training:
-- learning_rate: 5.689007559687745e-05
 - train_batch_size: 32
 - eval_batch_size: 32
 - seed: 42
@@ -78,9 +78,9 @@ The following hyperparameters were used during training:
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Recall | Precision |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
-| 0.7458        | 0.61  | 1500 | 0.7220          | 0.7672   | 0.7388 | 0.7672 | 0.7542    |
-| 0.561         | 1.22  | 3000 | 0.5900          | 0.8064   | 0.8050 | 0.8064 | 0.8105    |
-| 0.4937        | 1.83  | 4500 | 0.5322          | 0.8248   | 0.8202 | 0.8248 | 0.8214    |
 ### Framework versions

     metrics:
     - name: Accuracy
       type: accuracy
+      value: 0.7935375363131338
     - name: F1
       type: f1
+      value: 0.7782286513484494
     - name: Recall
       type: recall
+      value: 0.7935375363131338
     - name: Precision
       type: precision
+      value: 0.7838508007361574
 ---
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the consumer-finance-complaints dataset.
 It achieves the following results on the evaluation set:
+- Loss: 0.6228
+- Accuracy: 0.7935
+- F1: 0.7782
+- Recall: 0.7935
+- Precision: 0.7839
 ## Model description
 ### Training hyperparameters
 The following hyperparameters were used during training:
+- learning_rate: 0.00019154628432502008
 - train_batch_size: 32
 - eval_batch_size: 32
 - seed: 42
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Recall | Precision |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
+| 0.8624        | 0.61  | 1500 | 0.8468          | 0.7521   | 0.7215 | 0.7521 | 0.7083    |
+| 0.743         | 1.22  | 3000 | 0.7668          | 0.7651   | 0.7417 | 0.7651 | 0.7383    |
+| 0.6135        | 1.83  | 4500 | 0.6228          | 0.7935   | 0.7782 | 0.7935 | 0.7839    |
 ### Framework versions