End of training

README.md

@@ -10,23 +10,23 @@ metrics:
 - recall
 - f1
 model-index:
-- name: FairnessReciprocity_binary
+- name: IngroupLoyalty_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. -->
 
-# FairnessReciprocity_binary
+# IngroupLoyalty_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: 0.6999
-- Accuracy: 0.5972
-- Precision: 0.5651
-- Recall: 0.6674
-- F1: 0.6120
-- Auc: 0.6004
+- Loss: 0.6927
+- Accuracy: 0.6690
+- Precision: 0.6752
+- Recall: 0.7010
+- F1: 0.6879
+- Auc: 0.6676
 
 ## 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   | 125  | 0.6727          | 0.5782   | 0.5754    | 0.4337 | 0.4946 | 0.5715 |
-| No log        | 2.0   | 250  | 0.6749          | 0.5912   | 0.5579    | 0.68   | 0.6129 | 0.5953 |
-| No log        | 3.0   | 375  | 0.6999          | 0.5972   | 0.5651    | 0.6674 | 0.6120 | 0.6004 |
+| No log        | 1.0   | 127  | 0.6813          | 0.6601   | 0.7333    | 0.5448 | 0.6251 | 0.6649 |
+| No log        | 2.0   | 254  | 0.6369          | 0.6868   | 0.6683    | 0.7905 | 0.7243 | 0.6824 |
+| No log        | 3.0   | 381  | 0.6927          | 0.6690   | 0.6752    | 0.7010 | 0.6879 | 0.6676 |
 
 
 ### Framework versions

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:7af31cb6017a956839c51cc56c5422bf58da2fe6951bc16221cf8af2496f69ef
+oid sha256:80a9ef4d8995ef5946f172b8cb12a22a7a6738544621e46bf7a44662308654c6
 size 1421495416