End of training

README.md

@@ -15,10 +15,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # newsdata-bertimbal
 
-This model is a fine-tuned version of [neuralmind/bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) on the None dataset.
+This model is a fine-tuned version of [neuralmind/bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.7455
-- Accuracy: 0.8743
+- Loss: 0.3387
+- Accuracy: 0.9045
 
 ## Model description
 
@@ -38,28 +38,22 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 2e-05
-- train_batch_size: 2
+- train_batch_size: 4
 - eval_batch_size: 2
 - seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 16
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - num_epochs: 1
 
 ### Training results
 
-| Training Loss | Epoch  | Step  | Validation Loss | Accuracy |
-|:-------------:|:------:|:-----:|:---------------:|:--------:|
-| 0.8448        | 0.0859 | 5000  | 1.1296          | 0.8044   |
-| 0.7301        | 0.1718 | 10000 | 1.0056          | 0.8258   |
-| 0.6827        | 0.2577 | 15000 | 0.9388          | 0.8464   |
-| 0.6221        | 0.3436 | 20000 | 0.9358          | 0.8502   |
-| 0.5611        | 0.4295 | 25000 | 0.8983          | 0.8567   |
-| 0.5291        | 0.5155 | 30000 | 0.8503          | 0.8575   |
-| 0.4202        | 0.6014 | 35000 | 0.8353          | 0.8656   |
-| 0.5436        | 0.6873 | 40000 | 0.7476          | 0.8706   |
-| 0.4814        | 0.7732 | 45000 | 0.7863          | 0.8669   |
-| 0.4853        | 0.8591 | 50000 | 0.7284          | 0.8720   |
-| 0.39          | 0.9450 | 55000 | 0.7455          | 0.8743   |
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
+|:-------------:|:------:|:----:|:---------------:|:--------:|
+| 0.5125        | 0.2749 | 2000 | 0.4810          | 0.8749   |
+| 0.3874        | 0.5498 | 4000 | 0.3903          | 0.8938   |
+| 0.3425        | 0.8247 | 6000 | 0.3387          | 0.9045   |
 
 
 ### Framework versions