End of training

README.md

@@ -21,11 +21,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [facebook/bart-large-mnli](https://huggingface.co/facebook/bart-large-mnli) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.5797
-- F1: 0.8211
-- Precision: 0.8667
-- Recall: 0.78
-- Accuracy: 0.83
+- Loss: 0.5896
+- F1: 0.8467
+- Precision: 0.8529
+- Recall: 0.8406
+- Accuracy: 0.86
 
 ## Model description
 
@@ -55,23 +55,11 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch  | Step | Validation Loss | F1     | Precision | Recall | Accuracy |
-|:-------------:|:------:|:----:|:---------------:|:------:|:---------:|:------:|:--------:|
-| 0.5858        | 0.1266 | 10   | 0.5755          | 0.8627 | 0.8462    | 0.88   | 0.86     |
-| 0.583         | 0.2532 | 20   | 0.5953          | 0.7294 | 0.8857    | 0.62   | 0.77     |
-| 0.5986        | 0.3797 | 30   | 0.5831          | 0.8085 | 0.8636    | 0.76   | 0.82     |
-| 0.5829        | 0.5063 | 40   | 0.5860          | 0.8571 | 0.8182    | 0.9    | 0.85     |
-| 0.5975        | 0.6329 | 50   | 0.5814          | 0.7865 | 0.8974    | 0.7    | 0.81     |
-| 0.5881        | 0.7595 | 60   | 0.5745          | 0.8654 | 0.8333    | 0.9    | 0.86     |
-| 0.5712        | 0.8861 | 70   | 0.5878          | 0.7957 | 0.8605    | 0.74   | 0.81     |
-| 0.5536        | 1.0127 | 80   | 0.5853          | 0.8085 | 0.8636    | 0.76   | 0.82     |
-| 0.5726        | 1.1392 | 90   | 0.5766          | 0.8485 | 0.8571    | 0.84   | 0.85     |
-| 0.5843        | 1.2658 | 100  | 0.5762          | 0.8485 | 0.8571    | 0.84   | 0.85     |
-| 0.5704        | 1.3924 | 110  | 0.5761          | 0.8298 | 0.8864    | 0.78   | 0.84     |
-| 0.5714        | 1.5190 | 120  | 0.5860          | 0.7727 | 0.8947    | 0.68   | 0.8      |
-| 0.5688        | 1.6456 | 130  | 0.5815          | 0.8132 | 0.9024    | 0.74   | 0.83     |
-| 0.5723        | 1.7722 | 140  | 0.5760          | 0.8298 | 0.8864    | 0.78   | 0.84     |
-| 0.5716        | 1.8987 | 150  | 0.5797          | 0.8211 | 0.8667    | 0.78   | 0.83     |
+| Training Loss | Epoch | Step | Validation Loss | F1     | Precision | Recall | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:|:--------:|
+| 0.5721        | 0.625 | 10   | 0.5962          | 0.8429 | 0.8310    | 0.8551 | 0.8533   |
+| 0.5605        | 1.25  | 20   | 0.6015          | 0.768  | 0.8571    | 0.6957 | 0.8067   |
+| 0.5767        | 1.875 | 30   | 0.5896          | 0.8467 | 0.8529    | 0.8406 | 0.86     |
 
 
 ### Framework versions

adapter_config.json

@@ -25,8 +25,8 @@
   "rank_pattern": {},
   "revision": null,
   "target_modules": [
-    "q_proj",
     "k_proj",
+    "q_proj",
     "v_proj"
   ],
   "task_type": null,

adapter_model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:7239a9513b1fde269ea07d925ba3df87e6d54b13cbd8c1d42f516117d1fa9fce
-size 29720112
+oid sha256:6b6759fc215572e29248331687b19461b9c73f413442db30087d53cedf56e9a0
+size 29715788