update model card README.md

README.md

@@ -4,28 +4,26 @@ tags:
 - generated_from_trainer
 metrics:
 - accuracy
+- f1
+- precision
+- recall
 model-index:
 - name: LKD_Experience_CV4
   results: []
-widget:
-- text: Health A father donated a kidney to save his daughter. Because of his donation the physically active 53-yr-old man has been unable to obtain private health insurance
-  example_title: Example 1
-- text: AmItheAsshole AITA because I won't donate my kidney to my biological dad because I'm afraid of a surgery?
-  example_title: Example 2
-- text: AskReddit [Serious] If you somehow found out that you were a match for a total stranger who needed a kidney would you donate one of yours? What are your reasons?
-  example_title: Example 3
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 should probably proofread and complete it, then remove this comment. -->
 
-# LKD_Experience
+# LKD_Experience_CV4
 
-This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an dataset of Reddit comments and posts related to Living Kidney Donation (LKD).
-This model identifies documents as either describing a personal experience with LKD, or simply sharing news like headlines and noise/nonsense. Each document is a concatenation of three things:
-the name of the subreddit where the post was written, the title of the post, and if written, the full text of the post. 
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
 - Loss: 0.2443
 - Accuracy: 0.9244
+- F1: 0.9158
+- Precision: 0.9240
+- Recall: 0.9091
 
 ## Model description
 
@@ -54,13 +52,13 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|
-| No log        | 1.0   | 48   | 0.4809          | 0.7311   |
-| No log        | 2.0   | 96   | 0.3551          | 0.8908   |
-| No log        | 3.0   | 144  | 0.2712          | 0.9244   |
-| No log        | 4.0   | 192  | 0.2508          | 0.9244   |
-| No log        | 5.0   | 240  | 0.2443          | 0.9244   |
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| No log        | 1.0   | 48   | 0.4809          | 0.7311   | 0.6063 | 0.8532    | 0.6190 |
+| No log        | 2.0   | 96   | 0.3551          | 0.8908   | 0.8716 | 0.9157    | 0.8506 |
+| No log        | 3.0   | 144  | 0.2712          | 0.9244   | 0.9158 | 0.9240    | 0.9091 |
+| No log        | 4.0   | 192  | 0.2508          | 0.9244   | 0.9158 | 0.9240    | 0.9091 |
+| No log        | 5.0   | 240  | 0.2443          | 0.9244   | 0.9158 | 0.9240    | 0.9091 |
 
 
 ### Framework versions