Update README.md

README.md

@@ -19,15 +19,15 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.80
+      value: 0.86
 ---
 
 # twitter_sexismo-finetuned-exist2021
 
 This model is a fine-tuned version of [pysentimiento/robertuito-hate-speech](https://huggingface.co/pysentimiento/robertuito-hate-speech) on the EXIST dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.12
-- Accuracy: 0.80
+- Loss: 0.4
+- Accuracy: 0.86
 
 ## Model description
 
@@ -46,265 +46,25 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- my_learning_rate = 2E-6 
+- my_learning_rate = 5E-5 
 - my_adam_epsilon = 1E-8 
-- my_number_of_epochs = 15
+- my_number_of_epochs = 8
 - my_warmup = 3
 - my_mini_batch_size = 32
 - optimizer: AdamW with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 30
+- num_epochs: 8
 
 ### Training results
-
-======== Epoch 1 / 30 ========
-Training...
-  Batch    50  of    143.    Elapsed: 0:00:53.
-  Batch   100  of    143.    Elapsed: 0:01:45.
-
-  Average training loss: 0.39
-  Training epoch took: 0:02:29
-
-======== Epoch 2 / 30 ========
-Training...
-  Batch    50  of    143.    Elapsed: 0:00:52.
-  Batch   100  of    143.    Elapsed: 0:01:44.
-
-  Average training loss: 0.36
-  Training epoch took: 0:02:29
-
-======== Epoch 3 / 30 ========
-Training...
-  Batch    50  of    143.    Elapsed: 0:00:52.
-  Batch   100  of    143.    Elapsed: 0:01:44.
-
-  Average training loss: 0.34
-  Training epoch took: 0:02:29
-
-======== Epoch 4 / 30 ========
-Training...
-  Batch    50  of    143.    Elapsed: 0:00:52.
-  Batch   100  of    143.    Elapsed: 0:01:44.
-
-  Average training loss: 0.33
-  Training epoch took: 0:02:29
-
-======== Epoch 5 / 30 ========
-Training...
-  Batch    50  of    143.    Elapsed: 0:00:52.
-  Batch   100  of    143.    Elapsed: 0:01:44.
-
-  Average training loss: 0.31
-  Training epoch took: 0:02:29
-
-======== Epoch 6 / 30 ========
-Training...
-  Batch    50  of    143.    Elapsed: 0:00:52.
-  Batch   100  of    143.    Elapsed: 0:01:44.
-
-  Average training loss: 0.29
-  Training epoch took: 0:02:29
-
-======== Epoch 7 / 30 ========
-Training...
-  Batch    50  of    143.    Elapsed: 0:00:52.
-  Batch   100  of    143.    Elapsed: 0:01:44.
-
-  Average training loss: 0.28
-  Training epoch took: 0:02:29
-
-======== Epoch 8 / 30 ========
-Training...
-  Batch    50  of    143.    Elapsed: 0:00:52.
-  Batch   100  of    143.    Elapsed: 0:01:44.
-
-  Average training loss: 0.27
-  Training epoch took: 0:02:29
-
-======== Epoch 9 / 30 ========
-Training...
-  Batch    50  of    143.    Elapsed: 0:00:52.
-  Batch   100  of    143.    Elapsed: 0:01:44.
-
-  Average training loss: 0.25
-  Training epoch took: 0:02:28
-
-======== Epoch 10 / 30 ========
-Training...
-  Batch    50  of    143.    Elapsed: 0:00:52.
-  Batch   100  of    143.    Elapsed: 0:01:44.
-
-  Average training loss: 0.24
-  Training epoch took: 0:02:29
-
-======== Epoch 11 / 30 ========
-Training...
-  Batch    50  of    143.    Elapsed: 0:00:52.
-  Batch   100  of    143.    Elapsed: 0:01:44.
-
-  Average training loss: 0.23
-  Training epoch took: 0:02:28
-
-======== Epoch 12 / 30 ========
-Training...
-  Batch    50  of    143.    Elapsed: 0:00:52.
-  Batch   100  of    143.    Elapsed: 0:01:44.
-
-  Average training loss: 0.22
-  Training epoch took: 0:02:29
-
-======== Epoch 13 / 30 ========
-Training...
-  Batch    50  of    143.    Elapsed: 0:00:52.
-  Batch   100  of    143.    Elapsed: 0:01:44.
-
-  Average training loss: 0.21
-  Training epoch took: 0:02:29
-
-======== Epoch 14 / 30 ========
-Training...
-  Batch    50  of    143.    Elapsed: 0:00:52.
-  Batch   100  of    143.    Elapsed: 0:01:44.
-
-  Average training loss: 0.20
-  Training epoch took: 0:02:29
-
-======== Epoch 15 / 30 ========
-Training...
-  Batch    50  of    143.    Elapsed: 0:00:52.
-  Batch   100  of    143.    Elapsed: 0:01:44.
-
-  Average training loss: 0.19
-  Training epoch took: 0:02:29
-
-======== Epoch 16 / 30 ========
-Training...
-  Batch    50  of    143.    Elapsed: 0:00:52.
-  Batch   100  of    143.    Elapsed: 0:01:44.
-
-  Average training loss: 0.18
-  Training epoch took: 0:02:29
-
-======== Epoch 17 / 30 ========
-Training...
-  Batch    50  of    143.    Elapsed: 0:00:52.
-  Batch   100  of    143.    Elapsed: 0:01:44.
-
-  Average training loss: 0.17
-  Training epoch took: 0:02:29
-
-======== Epoch 18 / 30 ========
-Training...
-  Batch    50  of    143.    Elapsed: 0:00:52.
-  Batch   100  of    143.    Elapsed: 0:01:44.
-
-  Average training loss: 0.17
-  Training epoch took: 0:02:29
-
-======== Epoch 19 / 30 ========
-Training...
-  Batch    50  of    143.    Elapsed: 0:00:52.
-  Batch   100  of    143.    Elapsed: 0:01:44.
-
-  Average training loss: 0.16
-  Training epoch took: 0:02:29
-
-======== Epoch 20 / 30 ========
-Training...
-  Batch    50  of    143.    Elapsed: 0:00:52.
-  Batch   100  of    143.    Elapsed: 0:01:44.
-
-  Average training loss: 0.15
-  Training epoch took: 0:02:29
-
-======== Epoch 21 / 30 ========
-Training...
-  Batch    50  of    143.    Elapsed: 0:00:52.
-  Batch   100  of    143.    Elapsed: 0:01:44.
-
-  Average training loss: 0.15
-  Training epoch took: 0:02:29
-
-======== Epoch 22 / 30 ========
-Training...
-  Batch    50  of    143.    Elapsed: 0:00:52.
-  Batch   100  of    143.    Elapsed: 0:01:44.
-
-  Average training loss: 0.15
-  Training epoch took: 0:02:29
-
-======== Epoch 23 / 30 ========
-Training...
-  Batch    50  of    143.    Elapsed: 0:00:52.
-  Batch   100  of    143.    Elapsed: 0:01:44.
-
-  Average training loss: 0.14
-  Training epoch took: 0:02:29
-
-======== Epoch 24 / 30 ========
-Training...
-  Batch    50  of    143.    Elapsed: 0:00:52.
-  Batch   100  of    143.    Elapsed: 0:01:45.
-
-  Average training loss: 0.14
-  Training epoch took: 0:02:29
-
-======== Epoch 25 / 30 ========
-Training...
-  Batch    50  of    143.    Elapsed: 0:00:52.
-  Batch   100  of    143.    Elapsed: 0:01:44.
-
-  Average training loss: 0.14
-  Training epoch took: 0:02:29
-
-======== Epoch 26 / 30 ========
-Training...
-  Batch    50  of    143.    Elapsed: 0:00:52.
-  Batch   100  of    143.    Elapsed: 0:01:44.
-
-  Average training loss: 0.13
-  Training epoch took: 0:02:29
-
-======== Epoch 27 / 30 ========
-Training...
-  Batch    50  of    143.    Elapsed: 0:00:52.
-  Batch   100  of    143.    Elapsed: 0:01:44.
-
-  Average training loss: 0.13
-  Training epoch took: 0:02:29
-
-======== Epoch 28 / 30 ========
-Training...
-  Batch    50  of    143.    Elapsed: 0:00:52.
-  Batch   100  of    143.    Elapsed: 0:01:44.
-
-  Average training loss: 0.13
-  Training epoch took: 0:02:29
-
-======== Epoch 29 / 30 ========
-Training...
-  Batch    50  of    143.    Elapsed: 0:00:52.
-  Batch   100  of    143.    Elapsed: 0:01:44.
-
-  Average training loss: 0.12
-  Training epoch took: 0:02:29
-
-======== Epoch 30 / 30 ========
-Training...
-  Batch    50  of    143.    Elapsed: 0:00:52.
-  Batch   100  of    143.    Elapsed: 0:01:44.
-
-  Average training loss: 0.13
-  Training epoch took: 0:02:29
-
- precision    recall  f1-score   support
-
-           0       0.78      0.82      0.80       551
-           1       0.82      0.79      0.81       590
-
-    accuracy                           0.80      1141
-   macro avg       0.80      0.80      0.80      1141
-weighted avg       0.80      0.80      0.80      1141
+Epoch 	Training Loss 	Validation Loss 	Accuracy 	F1 	Precision 	Recall
+1 	      0.398400 	0.336709 	0.861404 	0.855311 	0.872897 	0.838420
+2 	      0.136100 	0.575872 	0.846491 	0.854772 	0.794753 	0.924596
+3 	      0.105600 	0.800685 	0.848246 	0.837863 	0.876471 	0.802513
+4 	      0.066500 	0.928388 	0.849123 	0.856187 	0.801252 	0.919210
+5 	      0.004500 	0.990655 	0.851754 	0.853680 	0.824415 	0.885099
+6 	      0.005500 	1.035315 	0.852632 	0.856164 	0.818331 	0.897666
+7 	      0.000200 	1.052970 	0.857895 	0.859375 	0.831933 	0.888689
+8 	      0.001700 	1.048338 	0.856140 	0.857143 	0.832487 	0.883303
 
 ### Framework versions