Model save

README.md

@@ -2,6 +2,8 @@
 base_model: aubmindlab/bert-large-arabertv02-twitter
 tags:
 - generated_from_trainer
+metrics:
+- accuracy
 model-index:
 - name: arabert-sentiment-classification
   results: []
@@ -13,6 +15,10 @@ should probably proofread and complete it, then remove this comment. -->
 # arabert-sentiment-classification
 
 This model is a fine-tuned version of [aubmindlab/bert-large-arabertv02-twitter](https://huggingface.co/aubmindlab/bert-large-arabertv02-twitter) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5525
+- Macro F1: 0.6558
+- Accuracy: 0.7957
 
 ## Model description
 
@@ -34,13 +40,21 @@ The following hyperparameters were used during training:
 - learning_rate: 2e-05
 - train_batch_size: 16
 - eval_batch_size: 128
-- seed: 42
+- seed: 25
 - gradient_accumulation_steps: 2
 - total_train_batch_size: 32
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - num_epochs: 2
 
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Macro F1 | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
+| No log        | 1.0   | 497  | 0.5462          | 0.6431   | 0.7925   |
+| 0.6202        | 2.0   | 994  | 0.5525          | 0.6558   | 0.7957   |
+
+
 ### Framework versions
 
 - Transformers 4.33.3

config.json

@@ -10,18 +10,18 @@
   "hidden_dropout_prob": 0.1,
   "hidden_size": 1024,
   "id2label": {
-    "0": "LABEL_0",
-    "1": "LABEL_1",
-    "2": "LABEL_2",
-    "3": "LABEL_3"
+    "0": "Positive",
+    "1": "Negative",
+    "2": "Neutral",
+    "3": "Mixed"
   },
   "initializer_range": 0.02,
   "intermediate_size": 4096,
   "label2id": {
-    "LABEL_0": 0,
-    "LABEL_1": 1,
-    "LABEL_2": 2,
-    "LABEL_3": 3
+    "Mixed": 3,
+    "Negative": 1,
+    "Neutral": 2,
+    "Positive": 0
   },
   "layer_norm_eps": 1e-12,
   "max_position_embeddings": 512,