anger_frustration_detection_5.2

README.md

@@ -1,7 +1,6 @@
 ---
 library_name: transformers
-license: mit
-base_model: pdelobelle/robbert-v2-dutch-base
+base_model: procit011/anger_frustration_detection_2
 tags:
 - generated_from_trainer
 metrics:
@@ -17,11 +16,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 # results
 
-This model is a fine-tuned version of [pdelobelle/robbert-v2-dutch-base](https://huggingface.co/pdelobelle/robbert-v2-dutch-base) on the None dataset.
+This model is a fine-tuned version of [procit011/anger_frustration_detection_2](https://huggingface.co/procit011/anger_frustration_detection_2) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1375
-- F1: 0.9786
-- Accuracy: 0.9795
+- Loss: 0.0800
+- F1: 0.9887
+- Accuracy: 0.9892
 
 ## Model description
 
@@ -53,9 +52,9 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|
-| 0.0613        | 1.0   | 830  | 0.1180          | 0.9747 | 0.9759   |
-| 0.0801        | 2.0   | 1660 | 0.1038          | 0.9823 | 0.9831   |
-| 0.0001        | 3.0   | 2490 | 0.1221          | 0.9798 | 0.9807   |
+| 0.0540        | 1.0   | 830  | 0.0693          | 0.9785 | 0.9795   |
+| 0.0271        | 2.0   | 1660 | 0.0783          | 0.9873 | 0.9880   |
+| 0.0001        | 3.0   | 2490 | 0.0809          | 0.9886 | 0.9892   |
 
 
 ### Framework versions

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:47db4031f5769493969d566ca0425e509c0573d2861bdc5cd4c4da27fb22ff48
+oid sha256:713a66c7d194832d772264d5f74baacdbdbf17b5abe82c75cf892919eae1eb07
 size 467078720