End of training

README.md

@@ -10,23 +10,23 @@ metrics:
 - recall
 - f1
 model-index:
-- name: Sympathy_binary
+- name: Self_Efficacy_binary
   results: []
 ---
 
 <!-- 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. -->
 
-# Sympathy_binary
+# Self_Efficacy_binary
 
 This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.6330
-- Accuracy: 0.6688
-- Precision: 0.6621
-- Recall: 0.7072
-- F1: 0.6839
-- Auc: 0.6683
+- Loss: 0.6822
+- Accuracy: 0.6468
+- Precision: 0.6816
+- Recall: 0.5996
+- F1: 0.6380
+- Auc: 0.6487
 
 ## Model description
 
@@ -57,9 +57,9 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Auc    |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
-| No log        | 1.0   | 134  | 0.6460          | 0.6119   | 0.6779    | 0.4457 | 0.5378 | 0.6141 |
-| No log        | 2.0   | 268  | 0.6462          | 0.6465   | 0.6277    | 0.7422 | 0.6802 | 0.6452 |
-| No log        | 3.0   | 402  | 0.6330          | 0.6688   | 0.6621    | 0.7072 | 0.6839 | 0.6683 |
+| No log        | 1.0   | 134  | 0.6634          | 0.6132   | 0.6849    | 0.4722 | 0.5590 | 0.6188 |
+| No log        | 2.0   | 268  | 0.6410          | 0.6393   | 0.6714    | 0.5978 | 0.6325 | 0.6410 |
+| No log        | 3.0   | 402  | 0.6822          | 0.6468   | 0.6816    | 0.5996 | 0.6380 | 0.6487 |
 
 
 ### Framework versions

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:caee7e5bb4fa8b521cb6f97e64e9faa4553040b573101de3627e0003ab4eaee9
+oid sha256:a23f4f2235d65d39aaeb4b8ae7c8650223d80b13b93fa9227cc4e5137d3b1b15
 size 1421495416