trainer: training complete at 2024-02-06 13:23:50.865104.

README.md

@@ -17,13 +17,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.6725
-- Claim: {'precision': 0.4435483870967742, 'recall': 0.3819444444444444, 'f1-score': 0.4104477611940298, 'support': 144.0}
-- Majorclaim: {'precision': 0.6166666666666667, 'recall': 0.5138888888888888, 'f1-score': 0.5606060606060607, 'support': 72.0}
-- Premise: {'precision': 0.7976470588235294, 'recall': 0.8625954198473282, 'f1-score': 0.8288508557457213, 'support': 393.0}
-- Accuracy: 0.7077
-- Macro avg: {'precision': 0.6192873708623234, 'recall': 0.5861429177268872, 'f1-score': 0.5999682258486039, 'support': 609.0}
-- Weighted avg: {'precision': 0.6925225974705789, 'recall': 0.7077175697865353, 'f1-score': 0.6982044339632925, 'support': 609.0}
+- Loss: 0.6785
+- Claim: {'precision': 0.47368421052631576, 'recall': 0.375, 'f1-score': 0.4186046511627907, 'support': 144.0}
+- Majorclaim: {'precision': 0.6923076923076923, 'recall': 0.5, 'f1-score': 0.5806451612903226, 'support': 72.0}
+- Premise: {'precision': 0.7900677200902935, 'recall': 0.8905852417302799, 'f1-score': 0.8373205741626795, 'support': 393.0}
+- Accuracy: 0.7225
+- Macro avg: {'precision': 0.6520198743081005, 'recall': 0.5885284139100934, 'f1-score': 0.6121901288719309, 'support': 609.0}
+- Weighted avg: {'precision': 0.7036999904062868, 'recall': 0.722495894909688, 'f1-score': 0.707967991832969, 'support': 609.0}
 
 ## Model description
 
@@ -52,15 +52,15 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Claim                                                                                                              | Majorclaim                                                                                                       | Premise                                                                                                           | Accuracy | Macro avg                                                                                                         | Weighted avg                                                                                                      |
-|:-------------:|:-----:|:----:|:---------------:|:------------------------------------------------------------------------------------------------------------------:|:----------------------------------------------------------------------------------------------------------------:|:-----------------------------------------------------------------------------------------------------------------:|:--------:|:-----------------------------------------------------------------------------------------------------------------:|:-----------------------------------------------------------------------------------------------------------------:|
-| No log        | 1.0   | 267  | 0.6970          | {'precision': 0.4307692307692308, 'recall': 0.19444444444444445, 'f1-score': 0.2679425837320574, 'support': 144.0} | {'precision': 0.5774647887323944, 'recall': 0.5694444444444444, 'f1-score': 0.5734265734265734, 'support': 72.0} | {'precision': 0.758985200845666, 'recall': 0.9134860050890585, 'f1-score': 0.8290993071593533, 'support': 393.0}  | 0.7028   | {'precision': 0.589073073449097, 'recall': 0.5591249646593158, 'f1-score': 0.556822821439328, 'support': 609.0}   | {'precision': 0.6599169424496689, 'recall': 0.7027914614121511, 'f1-score': 0.6661846848239006, 'support': 609.0} |
-| 0.7281        | 2.0   | 534  | 0.6725          | {'precision': 0.4435483870967742, 'recall': 0.3819444444444444, 'f1-score': 0.4104477611940298, 'support': 144.0}  | {'precision': 0.6166666666666667, 'recall': 0.5138888888888888, 'f1-score': 0.5606060606060607, 'support': 72.0} | {'precision': 0.7976470588235294, 'recall': 0.8625954198473282, 'f1-score': 0.8288508557457213, 'support': 393.0} | 0.7077   | {'precision': 0.6192873708623234, 'recall': 0.5861429177268872, 'f1-score': 0.5999682258486039, 'support': 609.0} | {'precision': 0.6925225974705789, 'recall': 0.7077175697865353, 'f1-score': 0.6982044339632925, 'support': 609.0} |
+| Training Loss | Epoch | Step | Validation Loss | Claim                                                                                                               | Majorclaim                                                                                                       | Premise                                                                                                           | Accuracy | Macro avg                                                                                                         | Weighted avg                                                                                                     |
+|:-------------:|:-----:|:----:|:---------------:|:-------------------------------------------------------------------------------------------------------------------:|:----------------------------------------------------------------------------------------------------------------:|:-----------------------------------------------------------------------------------------------------------------:|:--------:|:-----------------------------------------------------------------------------------------------------------------:|:----------------------------------------------------------------------------------------------------------------:|
+| No log        | 1.0   | 267  | 0.7119          | {'precision': 0.5072463768115942, 'recall': 0.24305555555555555, 'f1-score': 0.32863849765258213, 'support': 144.0} | {'precision': 0.5753424657534246, 'recall': 0.5833333333333334, 'f1-score': 0.5793103448275863, 'support': 72.0} | {'precision': 0.7687366167023555, 'recall': 0.9134860050890585, 'f1-score': 0.8348837209302326, 'support': 393.0} | 0.7159   | {'precision': 0.6171084864224582, 'recall': 0.5799582979926492, 'f1-score': 0.580944187803467, 'support': 609.0}  | {'precision': 0.6840420790790506, 'recall': 0.715927750410509, 'f1-score': 0.6849648453450565, 'support': 609.0} |
+| 0.7298        | 2.0   | 534  | 0.6785          | {'precision': 0.47368421052631576, 'recall': 0.375, 'f1-score': 0.4186046511627907, 'support': 144.0}               | {'precision': 0.6923076923076923, 'recall': 0.5, 'f1-score': 0.5806451612903226, 'support': 72.0}                | {'precision': 0.7900677200902935, 'recall': 0.8905852417302799, 'f1-score': 0.8373205741626795, 'support': 393.0} | 0.7225   | {'precision': 0.6520198743081005, 'recall': 0.5885284139100934, 'f1-score': 0.6121901288719309, 'support': 609.0} | {'precision': 0.7036999904062868, 'recall': 0.722495894909688, 'f1-score': 0.707967991832969, 'support': 609.0}  |
 
 
 ### Framework versions
 
-- Transformers 4.33.0
-- Pytorch 2.0.1+cu118
-- Datasets 2.14.4
-- Tokenizers 0.13.3
+- Transformers 4.37.1
+- Pytorch 2.1.2+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.1

config.json

@@ -31,7 +31,7 @@
   "position_embedding_type": "absolute",
   "problem_type": "single_label_classification",
   "torch_dtype": "float32",
-  "transformers_version": "4.33.0",
+  "transformers_version": "4.37.1",
   "type_vocab_size": 1,
   "use_cache": true,
   "vocab_size": 50265

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b255249fe64b38dcdc3ef3cc978c7ccddb34bb9caf791234d88d8e2ff294b46c
+size 498615900

tokenizer.json

@@ -14,7 +14,7 @@
       "single_word": false,
       "lstrip": false,
       "rstrip": false,
-      "normalized": false,
+      "normalized": true,
       "special": true
     },
     {
@@ -23,7 +23,7 @@
       "single_word": false,
       "lstrip": false,
       "rstrip": false,
-      "normalized": false,
+      "normalized": true,
       "special": true
     },
     {
@@ -32,7 +32,7 @@
       "single_word": false,
       "lstrip": false,
       "rstrip": false,
-      "normalized": false,
+      "normalized": true,
       "special": true
     },
     {
@@ -41,7 +41,7 @@
       "single_word": false,
       "lstrip": false,
       "rstrip": false,
-      "normalized": false,
+      "normalized": true,
       "special": true
     },
     {

tokenizer_config.json

@@ -1,5 +1,47 @@
 {
   "add_prefix_space": true,
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<s>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "1": {
+      "content": "<pad>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "2": {
+      "content": "</s>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "3": {
+      "content": "<unk>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "50264": {
+      "content": "<mask>",
+      "lstrip": true,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
   "bos_token": "<s>",
   "clean_up_tokenization_spaces": true,
   "cls_token": "<s>",

training_args.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:d659f2c05c60f157d7a0ec6dc0d517af668613072c7024daf433342a786fe682
-size 4027
+oid sha256:4a690db7c3d609d9dd4b2b8bbcdde8143de2fe10df2ac70b85dd0c33404a7370
+size 4728