End of training

README.md

@@ -21,11 +21,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [cardiffnlp/twitter-roberta-large-hate-latest](https://huggingface.co/cardiffnlp/twitter-roberta-large-hate-latest) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.4394
-- Accuracy: 0.8521
-- Precision: 0.7814
-- Recall: 0.7733
-- F1: 0.7764
+- Loss: 0.8408
+- Accuracy: 0.8023
+- Precision: 0.7245
+- Recall: 0.7129
+- F1: 0.7177
 
 ## Model description
 
@@ -44,25 +44,30 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 1e-05
+- learning_rate: 5e-05
 - train_batch_size: 32
 - eval_batch_size: 128
 - seed: 42
-- gradient_accumulation_steps: 4
-- total_train_batch_size: 128
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 64
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 5
+- num_epochs: 10
 
 ### Training results
 
-| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
-|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
-| 0.8983        | 0.9912 | 56   | 0.7694          | 0.7359   | 0.6713    | 0.6012 | 0.6247 |
-| 0.7237        | 2.0    | 113  | 0.5778          | 0.7987   | 0.7241    | 0.6824 | 0.6913 |
-| 0.5471        | 2.9912 | 169  | 0.4937          | 0.8297   | 0.7491    | 0.7530 | 0.7503 |
-| 0.5403        | 4.0    | 226  | 0.4589          | 0.8424   | 0.7705    | 0.7575 | 0.7626 |
-| 0.5452        | 4.9558 | 280  | 0.4394          | 0.8521   | 0.7814    | 0.7733 | 0.7764 |
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.9091        | 1.0   | 113  | 0.8078          | 0.7034   | 0.3788    | 0.4083 | 0.3878 |
+| 1.1008        | 2.0   | 226  | 0.9036          | 0.6510   | 0.2624    | 0.3397 | 0.2841 |
+| 0.7624        | 3.0   | 339  | 0.6444          | 0.7844   | 0.7015    | 0.6274 | 0.6544 |
+| 0.5512        | 4.0   | 452  | 0.5075          | 0.8342   | 0.7675    | 0.7453 | 0.7463 |
+| 0.5258        | 5.0   | 565  | 0.3519          | 0.8858   | 0.8263    | 0.8081 | 0.8163 |
+| 0.3489        | 6.0   | 678  | 0.3154          | 0.9011   | 0.8612    | 0.8260 | 0.8399 |
+| 0.3182        | 7.0   | 791  | 0.2394          | 0.9295   | 0.8985    | 0.8864 | 0.8895 |
+| 0.2263        | 8.0   | 904  | 0.1722          | 0.9502   | 0.9092    | 0.9223 | 0.9143 |
+| 0.2024        | 9.0   | 1017 | 0.1252          | 0.9684   | 0.9474    | 0.9441 | 0.9457 |
+| 0.1757        | 10.0  | 1130 | 0.1101          | 0.9736   | 0.9592    | 0.9506 | 0.9548 |
 
 
 ### Framework versions