Colabng/twitter_bank_scam_classifier

README.md

@@ -20,9 +20,9 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.6814
-- Accuracy: 0.59
-- Auc: 0.62
+- Loss: 0.7566
+- Accuracy: 0.64
+- Auc: 0.67
 
 ## Model description
 
@@ -53,8 +53,8 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | Auc  |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:----:|
-| 0.7235        | 1.0   | 11   | 0.6819          | 0.55     | 0.63 |
-| 0.6736        | 2.0   | 22   | 0.6814          | 0.59     | 0.62 |
+| 0.7449        | 1.0   | 11   | 0.7669          | 0.5      | 0.66 |
+| 0.7084        | 2.0   | 22   | 0.7566          | 0.64     | 0.67 |
 
 
 ### Framework versions

adapter_config.json

@@ -28,9 +28,9 @@
   "rank_pattern": {},
   "revision": null,
   "target_modules": [
-    "value",
+    "key",
     "query",
-    "key"
+    "value"
   ],
   "task_type": "SEQ_CLS",
   "trainable_token_indices": null,

adapter_model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:f8eae5690ca846f6c5922b338ce42337d604a015c7f0f635b388e78d8b59c6ed
+oid sha256:fd6ab6fde9b36810e90f70609a7a3ee618b9b69b51b0a9408922da72f0b9a579
 size 95583552

runs/Sep06_21-31-33_7aceba5bb9af/events.out.tfevents.1757194293.7aceba5bb9af

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:21042d29ef9c5a5dcc5caae3154b554e14873eaf189cebab5faa995df4537491
+size 6537

training_args.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:31ccc08f37661a9d723968779706c695e4c5dc6dc0728956ad18207d7e168c86
+oid sha256:4daa0d8d24dab83655ff5277850650b8124d530a5ed73a0f7f4b2731a444325c
 size 5777