End of training

README.md

@@ -10,23 +10,23 @@ metrics:
 - recall
 - f1
 model-index:
-- name: Neuro_binary
+- name: HarmCare_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. -->
 
-# Neuro_binary
+# HarmCare_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: 0.5602
-- Accuracy: 0.7418
-- Precision: 0.7431
-- Recall: 0.7472
-- F1: 0.7452
-- Auc: 0.7418
+- Loss: 0.6675
+- Accuracy: 0.6433
+- Precision: 0.6315
+- Recall: 0.7438
+- F1: 0.6831
+- Auc: 0.6398
 
 ## 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  | 0.5239          | 0.7428   | 0.7367    | 0.7638 | 0.75   | 0.7426 |
-| No log        | 2.0   | 268  | 0.5155          | 0.7428   | 0.7454    | 0.7454 | 0.7454 | 0.7428 |
-| No log        | 3.0   | 402  | 0.5602          | 0.7418   | 0.7431    | 0.7472 | 0.7452 | 0.7418 |
+| No log        | 1.0   | 127  | 0.6639          | 0.6087   | 0.6074    | 0.6864 | 0.6445 | 0.6060 |
+| No log        | 2.0   | 254  | 0.6713          | 0.5988   | 0.5723    | 0.8853 | 0.6952 | 0.5889 |
+| No log        | 3.0   | 381  | 0.6675          | 0.6433   | 0.6315    | 0.7438 | 0.6831 | 0.6398 |
 
 
 ### Framework versions

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:458ae7586f3dfcb3ba699fd72a51792b816322229c91c1b72064453e34214467
+oid sha256:43e98b4c0016bd81c35fc24ac248ff1351e835dc37faf03b71efe0462c08c1eb
 size 1421495416