metacognitive_cls_10

README.md

@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1544
-- Accuracy: 0.9477
-- F1: 0.8277
-- Precision: 0.8781
-- Recall: 0.7827
+- Loss: 0.1024
+- Accuracy: 0.9640
+- F1: 0.8326
+- Precision: 0.8742
+- Recall: 0.7947
 
 ## Model description
 
@@ -56,18 +56,18 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
-| 0.692         | 1.0   | 61   | 0.6603          | 0.6342   | 0.2154 | 0.1642    | 0.3131 |
-| 0.5269        | 2.0   | 122  | 0.3794          | 0.8719   | 0.5059 | 0.6632    | 0.4089 |
-| 0.3652        | 3.0   | 183  | 0.3409          | 0.8770   | 0.4737 | 0.7552    | 0.3450 |
-| 0.3282        | 4.0   | 244  | 0.3081          | 0.8940   | 0.5586 | 0.8397    | 0.4185 |
-| 0.2936        | 5.0   | 305  | 0.2756          | 0.9022   | 0.5892 | 0.9013    | 0.4377 |
-| 0.2529        | 6.0   | 366  | 0.2550          | 0.9129   | 0.6805 | 0.8265    | 0.5783 |
-| 0.2141        | 7.0   | 427  | 0.2388          | 0.9221   | 0.7361 | 0.8061    | 0.6773 |
-| 0.1802        | 8.0   | 488  | 0.2059          | 0.9278   | 0.7413 | 0.8707    | 0.6454 |
-| 0.1494        | 9.0   | 549  | 0.2064          | 0.9221   | 0.7532 | 0.7657    | 0.7412 |
-| 0.1179        | 10.0  | 610  | 0.1786          | 0.9401   | 0.8098 | 0.8245    | 0.7955 |
-| 0.0941        | 11.0  | 671  | 0.1589          | 0.9457   | 0.8227 | 0.8632    | 0.7859 |
-| 0.0816        | 12.0  | 732  | 0.1544          | 0.9477   | 0.8277 | 0.8781    | 0.7827 |
+| 0.6685        | 1.0   | 76   | 0.6265          | 0.7931   | 0.0543 | 0.0559    | 0.0528 |
+| 0.45          | 2.0   | 152  | 0.2973          | 0.8983   | 0.3275 | 0.6410    | 0.2199 |
+| 0.2947        | 3.0   | 228  | 0.2671          | 0.9069   | 0.4910 | 0.6385    | 0.3988 |
+| 0.2561        | 4.0   | 304  | 0.2246          | 0.9234   | 0.5323 | 0.8516    | 0.3871 |
+| 0.2201        | 5.0   | 380  | 0.1926          | 0.9442   | 0.6988 | 0.8909    | 0.5748 |
+| 0.1896        | 6.0   | 456  | 0.1704          | 0.9439   | 0.6828 | 0.9385    | 0.5367 |
+| 0.1574        | 7.0   | 532  | 0.1468          | 0.9515   | 0.7452 | 0.9110    | 0.6305 |
+| 0.1203        | 8.0   | 608  | 0.1213          | 0.9591   | 0.8056 | 0.8653    | 0.7537 |
+| 0.0924        | 9.0   | 684  | 0.1119          | 0.9634   | 0.8290 | 0.8734    | 0.7889 |
+| 0.0771        | 10.0  | 760  | 0.1073          | 0.9620   | 0.8206 | 0.8767    | 0.7713 |
+| 0.067         | 11.0  | 836  | 0.1016          | 0.9657   | 0.8415 | 0.8762    | 0.8094 |
+| 0.0609        | 12.0  | 912  | 0.1024          | 0.9640   | 0.8326 | 0.8742    | 0.7947 |
 
 
 ### Framework versions

config.json

@@ -15,11 +15,15 @@
     "4": "Examples",
     "5": "Comparisons",
     "6": "Explain",
-    "7": "MA"
+    "7": "MA",
+    "8": "AllExplain",
+    "9": "ALLComparison"
   },
   "initializer_range": 0.02,
   "intermediate_size": 4096,
   "label2id": {
+    "ALLComparison": 9,
+    "AllExplain": 8,
     "Comparisons": 5,
     "Examples": 4,
     "Explain": 6,

model.safetensors

@@ -1,3 +1,3 @@
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+oid sha256:ffc0406d895227a3406c4ce8a3e59f5778ad2ffa6bbbfe98ca7ca9e25df2d1ea
+size 1740337248

training_args.bin

@@ -1,3 +1,3 @@
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 size 5048