End of training

README.md

@@ -24,16 +24,16 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9436234263820471
+      value: 0.9425287356321839
     - name: F1
       type: f1
-      value: 0.8571428571428571
+      value: 0.8543689320388349
     - name: Precision
       type: precision
-      value: 0.8778409090909091
+      value: 0.875
     - name: Recall
       type: recall
-      value: 0.8373983739837398
+      value: 0.8346883468834688
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -43,11 +43,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the offenseval_2020 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1829
-- Accuracy: 0.9436
-- F1: 0.8571
-- Precision: 0.8778
-- Recall: 0.8374
+- Loss: 0.2500
+- Accuracy: 0.9425
+- F1: 0.8544
+- Precision: 0.875
+- Recall: 0.8347
 
 ## Model description
 
@@ -67,20 +67,29 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 5e-05
-- train_batch_size: 8
-- eval_batch_size: 8
+- train_batch_size: 16
+- eval_batch_size: 16
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 3.0
+- num_epochs: 12
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
-| 0.1799        | 1.0   | 980  | 0.1848          | 0.9299   | 0.8298 | 0.8146    | 0.8455 |
-| 0.0951        | 2.0   | 1960 | 0.1136          | 0.9398   | 0.8397 | 0.9085    | 0.7805 |
-| 0.0429        | 3.0   | 2940 | 0.1829          | 0.9436   | 0.8571 | 0.8778    | 0.8374 |
+| No log        | 1.0   | 490  | 0.1377          | 0.9321   | 0.8263 | 0.8551    | 0.7995 |
+| 0.1418        | 2.0   | 980  | 0.0967          | 0.9321   | 0.8121 | 0.9210    | 0.7263 |
+| 0.0898        | 3.0   | 1470 | 0.1082          | 0.9442   | 0.8517 | 0.9185    | 0.7940 |
+| 0.0595        | 4.0   | 1960 | 0.1530          | 0.9338   | 0.8358 | 0.8370    | 0.8347 |
+| 0.0405        | 5.0   | 2450 | 0.1559          | 0.9442   | 0.8579 | 0.8825    | 0.8347 |
+| 0.0194        | 6.0   | 2940 | 0.2175          | 0.9398   | 0.8541 | 0.8364    | 0.8726 |
+| 0.0153        | 7.0   | 3430 | 0.1994          | 0.9392   | 0.8452 | 0.8707    | 0.8211 |
+| 0.0102        | 8.0   | 3920 | 0.2154          | 0.9403   | 0.8541 | 0.8439    | 0.8645 |
+| 0.0093        | 9.0   | 4410 | 0.2296          | 0.9409   | 0.8470 | 0.8872    | 0.8103 |
+| 0.0047        | 10.0  | 4900 | 0.2406          | 0.9420   | 0.8524 | 0.8768    | 0.8293 |
+| 0.0038        | 11.0  | 5390 | 0.2530          | 0.9436   | 0.8591 | 0.8674    | 0.8509 |
+| 0.0051        | 12.0  | 5880 | 0.2500          | 0.9425   | 0.8544 | 0.875     | 0.8347 |
 
 
 ### Framework versions

pytorch_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:95bdefe2add6f624c7af06664ab6fca5be1239298075c2d7f94fdc5ae36a70a5
+oid sha256:9d34232aba4ceb1b353acace73cd728a10bf9e21c5951c2e6dbbcfa63ffc027c
 size 540847921